28 jobs found

Job Description Job Description Description: Direct Hire Hybrid schedule in Plano, TX Comp range: $150-180K 15% travel (including int 'l ) MUST BE US CITIZEN or GREEN CARD HOLDER (No C2C) JOB DESCRIPTION Architect the Future of Enterprise Intelligence The Senior Data Architect provides technical leadership across the company's data landscape shaping enterprise data strategy and designing scalable, secure, and well governed data platforms that power analytics, AI/ML, and intelligent applications. This role spans traditional data management (DBMS, data modeling, warehousing, governance) and modern cloud native/AI data engineering on AWS, including bronze, silver, gold patterns, Generation (RAG) for LLMs, and data products that serve Cloud-native SaaS application teams at global scale. You will collaborate with business stakeholders, data scientists, engineers, and platform teams to translate use cases into target data architectures, ensuring performance, reliability, security, and cost efficiency at global scale. What You'll do Modern Data Platform on One or More Cloud Platforms Architect end-to-end pipelines across from raw to polished layers using Cloud native services such as S3, Glue (ETL & Data Catalog), Lake Formation, Redshift, Athena, EMR/Spark, Kinesis/MSK, Step Functions, Lambda, EventBridge. Define storage/format strategies (e.g., Parquet/Delta/Apache Iceberg) and partitioning, compaction, and indexing for performance and cost. Implement row/ column level security, encryption (KMS), secrets management, and fine-grained authorization via IAM/Lake Formation. AI/ML & Amazon Bedrock Data Foundations Design datasets and feature/knowledge layers to support SageMaker training/inference and Amazon Bedrock applications (e.g., Knowledge Bases, Guardrails, Agents, and Invoke Model/Converse orchestration). Lead RAG architectures (chunking, embeddings, retrieval) using vector databases such as Amazon OpenSearch Serverless (vector search) or Aurora PostgreSQL + pgvector; define evaluation and feedback loops to improve answer quality. Set prompt, context, and token budget standards; guide teams on safe data handling for LLMs (PII redaction, policy driven filters, secured context injection). Tradition Data Architecture & DBMS Excellence Provide deep expertise in relational and NoSQL systems: SQL Server, PostgreSQL, MongoDB, including schema design, indexing, query/perf tuning, replication, partitioning, and HA/DR. Design and govern EDW/ Lakehouse/ODS patterns; integrate with .NET/C# services and Angular frontends via well designed APIs and data contracts. Integration, Interoperability & Application Alignment Define API and data contract standards (REST/GraphQL, Protobuf/Avro/JSON), ensuring consistent versioning and backward compatibility for .NET/C# and Angular consumers. Orchestrate ingestion from SAP, Salesforce, IoT/telemetry, external data sources, and partner ecosystems; standardize CDC and streaming patterns (e.g., MSK/Kinesis, DMS, Glue). Partner with Solution/Platform Architects to ensure microservices and event driven designs are data efficient and observability ready. Data Governance, Quality & Observability Implement data governance (policies, stewardship, data classification), cataloging (Glue Data Catalog), lineage (Open Lineage compatible), and quality (rules, thresholds, SLAs/SLOs). Embed monitoring & cost governance (CloudWatch, CloudTrail, Cost Explorer, Lake Formation audit, data access logs) and drive continuous optimization (storage tiers, compaction, pruning). Security, Compliance & Risk Enforce privacy and compliance (e.g., GDPR) with data minimization, tokenization, masking, and access controls across environments. Define secure patterns for model inputs/outputs (LLM safety), prompt hygiene, and guardrails to prevent leakage or misuse. Delivery Leadership & Collaboration Produce architecture blueprints, target state designs, and build/run guardrails; guide PoCs and pilots to derisk solutions. Mentor data engineers, analysts, and junior architects; lead design reviews, threat modeling, and cost/performance reviews. Communicate clearly with technical and nontechnical stakeholders, champion a culture of engineering excellence and learning. What You'll Bring This position is not eligible for employer-sponsored work authorization or visa sponsorship (including initial, transfer, or extension), and candidates must be authorized to work in the United States at the time of application and remain authorized for the duration of employment without the need for sponsorship. Bachelor's or master's in computer science, Information Systems, Data Engineering, or related field (or equivalent experience). Relevant certifications a plus (e.g., AWS Data Analytics/Solutions Architect preferred). 10+ years designing and delivering enterprise data solutions, including hands-on work with both traditional DBMS and cloud native data platforms. 5+ years building on cloud platforms with production experience in several of: S3, Glue, Lake Formation, Redshift, Athena, EMR/Spark, Kinesis/MSK, Lambda, Step Functions, EventBridge, SageMaker. Demonstrated expertise implementing data propagation Lakehouse patterns and governance at scale. Proven track record supporting AI/ML workloads (feature stores, model data pipelines) and delivering RAG solutions with vector search on AWS. Strong SQL and Python; proficiency in data modeling - IFC (preferred), 3NF, dimensional/star, data vault, etc. DBMS: SQL Server, PostgreSQL (schema, indexing, query planning, replication/HA, partitioning, backup/restore). Data Engineering: Spark/EMR, Glue (ETL/ELT & Studio), Airflow/Step Functions orchestration, Parquet/Delta/Iceberg. Streaming/CDC: MSK/Kinesis, DMS (change data capture), event driven patterns. Security & Governance: IAM, KMS, Lake Formation, Secrets Manager, data masking/tokenization, RBAC/ABAC. AI/LLM enablement: Amazon Bedrock (Knowledge Bases, Guardrails, Agents), embeddings, chunking, retrieval, prompt design, token optimization, evaluation loops. Observability & FinOps: Cloud logs/metrics, lineage/quality SLAs, cost controls (storage/compute), workload rightsizing. DevOps/MLOps/IaC: Git, CI/CD for data pipelines; Terraform/CDK; environment promotion; artifact/versioning ; blue/green or canary for data jobs. Preferred Skills Experience with Redshift RA3/Spectrum, materialized views, workload management, and federated queries (Athena/Glue). Familiarity with Power BI / Microsoft Fabric and Amazon Quick Sight; semantic modeling and governance for BI. Exposure to privacy enhancing technologies (anonymization, differential privacy), policy as code, and guardrail frameworks. Experience working with geographically distributed teams and regulated data. Strategic thinking with the ability to balance short-term increments and long term architecture. Excellent written and verbal communication, facilitation of architecture decisions, and stakeholder alignment. Mentoring mindset and demonstrated influence without authority across cross functional teams. System One, and its subsidiaries including Joulé, ALTA IT Services, and Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law. Ref: Tulsa

Job Description Principal AI Solutions Architect About Us MathCo (TheMathCompany) is a global Enterprise AI and Analytics company trusted by Fortune 500 and Global 2000 enterprises for data-driven decision-making. Founded in 2016, MathCo builds custom AI and advanced analytics solutions focused on enterprise problem-solving through its innovative hybrid model. NucliOS, MathCo's proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. We foster an open, transparent, and collaborative culture with no barriers, making MathCo a great place to work. We offer exciting growth opportunities and value capabilities and attitude over experience-enabling our Mathemagicians to truly Leave a Mark. Role Overview We are seeking a Principal AI Solutions Architect with deep, hands-on experience building production GenAI and agentic systems. You will be the senior technical voice on our US AI engagements focused on AI-ready data and context foundations and on operating AI on an enterprise scale, across CPG, Retail, Life Sciences and other industries, turning that expertise into scalable applications that solve complex business problems. This is not a research role. We are looking for someone who has designed and implemented production AI solutions and knows what it takes to move from POCs to enterprise-scale applications. You will work on client opportunities from the first conversation through proposal, alongside our client and sales leaders, and with MathCo's global architecture and delivery teams, including our teams in India, so that every solution is technically sound and deliverable. The ideal candidate has worked deeply with LLMs, knowledge graphs, context engineering, agentic systems, AI orchestration, and modern AI and data platforms. What You'll Do Serve as a GenAI technical authority Provide senior technical credibility in strategic client and solutioning conversations with CTOs, CIOs, Chief Data Officers, AI leaders and business executives. Translate complex AI concepts into clear business implications, trade-offs and recommendations. Lead in-depth technical discussions on context layer, knowledge graphs, agents and AI operations in live client settings. Architect enterprise AI solutions Define end-to-end architectures that bring together LLMs, knowledge graphs, retrieval and context layers, agents, tools, orchestration frameworks and enterprise data. Develop architecture patterns that take AI applications from prototype to production. Evaluate options against business requirements, performance, scalability, security, maintainability and cost. Provide technical direction to engineering and delivery teams, and build a working prototype or demo when needed. Author and present the technical sections of proposals: architecture, phasing, assumptions and effort estimates. Build reusable reference architectures, scoping frameworks and platform-specific demos. Connect AI to business outcomes Work with clients to understand business processes and identify where AI can materially change how work gets done. Partner with business and consulting teams to shape AI opportunities into technically viable solutions. Build the business case: quantify the value and ROI of AI programs Design the data and context foundation Design how context is assembled and managed for AI systems across structured and unstructured enterprise knowledge. Design solutions using knowledge graphs, retrieval, memory, tools and other mechanisms that improve the relevance and reliability of LLM applications. Design the data foundation under AI applications: lakehouse and data-platform architecture, metadata and catalogs, semantic layers, data quality and access controls. Architect agentic systems, including tools, orchestration, guardrails and supporting infrastructure. Operationalize AI at enterprise scale Shape AI operations solutions: LLMOps, evaluation and monitoring, guardrails, and model and agent lifecycle management. Advise on AI cost: token usage and optimization, model selection and routing, and infrastructure trade-offs. Advise on AI governance and risk, including frameworks such as NIST AI RMF and the EU AI Act, data privacy (including HIPAA), security and audit. Develop points of view on emerging AI-at-scale topics with MathCo's innovation teams. What We're Looking For 10+ years in AI, machine learning, data or enterprise architecture, including 2+ years designing and shipping production GenAI / LLM applications. Hands-on experience building sophisticated AI applications with commercial and/or open-source foundation models. Strong knowledge of LLM application architecture, context engineering, knowledge graphs, retrieval and grounding, agentic AI and multi-step workflows, AI orchestration, and enterprise data integration. Working knowledge of lakehouse and data platforms (e.g., Databricks, Snowflake, BigQuery), semantic layers, metadata and catalogs. Working knowledge of evaluation, observability and LLMOps, AI cost optimization, and AI governance, privacy and security. Familiarity with leading model ecosystems (OpenAI, Anthropic, Google) and hyperscaler AI services Pre-sales, solutions engineering or consulting experience, including authoring and defending the technical sections of proposals and SOWs. Ability to explain why specific technical choices were made, to engineers and executives alike. Experience working with global delivery teams across time zones. Exposure to data and AI use cases in CPG, Retail or Life Sciences. What Will Differentiate You The strongest candidates will be able to demonstrate all three of the following: 1. Technical depth You understand the mechanics of modern AI systems deeply enough to engage with senior AI engineers, scientists and architects. 2. Architecture and implementation experience You can whiteboard an end-to-end AI architecture and explain how it would actually be implemented, including the decisions and trade-offs required to make it successful at enterprise scale. 3. Executive and client credibility You can take that same architecture into a client conversation and explain it in a way that builds confidence with both business and technical executives - including a value case a CFO would sign off on. What Success Looks Like You are the trusted technical voice on our AI data, context and scale engagements. Your proposal architectures are credible, clearly scoped and deliverable. The reference architectures, ROI models and demos you build are used across the team. You bring new points of view on operating AI at scale to our clients. Being a Mathemagician Embody MathCo's values of openness, ownership, and impact. Contribute actively to internal mentorship, innovation, and team development. Champion diversity, equity, and inclusion by valuing a variety of perspectives in problem-solving. Why Join Us? MathCo is recognized globally as a leader in enterprise AI and analytics: Leader in Generative AI Service Providers - PeMa Quadrant (AIMResearch) Named among North America's Inspiring Workplaces Accredited for Inclusive Practices - Great Place to Work Institute, India Recognized for DEIB Excellence - India's Best Workplaces for DEIB To learn more, visit

Job Description Job Description Indent : PSL308118-1-3 Role : Enterprise Architect- Real-Time Data Engineering & Streaming Platforms Location : Whippany, NJ (Hybrid) Salary : $150k - $160k Category Skills Must-haveStreaming platforms, Java, Kafka/Flink/Spark, distributed systems, real-time production opsNice-to-haveDatabricks, cloud-native stack, CI/CD, financial domain experience, stakeholder communication About the role Join us as Vice President, Real-Time Data Engineering & Streaming Platforms, where you will lead the design and evolution of enterprise-grade streaming and real-time data capabilities that underpin critical business, regulatory, and client outcomes. This is a hands-on engineering leadership role for someone who can write production-quality software, shape technical direction, lead teams, and run low-latency, resilient, and secure streaming platforms at scale in production. This role is suited to a senior engineering leader with deep expertise in streaming architectures and large-scale data platforms, combined with the ability to lead engineers while remaining close to the code, architecture, delivery, and production operating model. You will be expected to make strong technical decisions, contribute directly to solution design and implementation when needed, coach engineers through complex problems, and maintain high standards across software quality, platform resilience, scalability, observability, and operational execution. What you'll do Lead the architecture, design, development, and operational stewardship of real-time streaming and data platform capabilities, remaining hands-on in key technical decisions and implementation where appropriate. Write, review, and guide high-quality production code for critical platform components, setting the bar for engineering standards, maintainability, resilience, and performance. Lead and develop engineering teams, providing technical direction, coaching, and delivery leadership while creating a culture of accountability, ownership, and continuous improvement. Own the design and production operation of resilient, low-latency streaming solutions that process critical financial events with strong guarantees for correctness, recoverability, observability, scalability, and control. Run streaming platforms at scale, including responsibility for production health, capacity, reliability, incident response, recovery, and continuous service improvement. Partner with business, product, architecture, and control stakeholders to shape roadmaps, solve complex engineering problems, and align platform delivery with business and regulatory requirements. Drive platform modernization across streaming, event processing, and data movement, balancing hands-on technical contribution with leadership across delivery priorities and dependencies. Establish strong engineering disciplines across testing, code review, release management, observability, incident response, capacity planning, and production readiness for real-time workloads. To be successful you should have experience with: Deep experience designing, building, and operating real-time data platforms, streaming architectures, and distributed systems in complex enterprise environments. At least 5 years of hands-on experience running real-time streaming solutions in production at scale, with accountability for reliability, performance, observability, recovery, and operational stability. Strong software engineering capability, with fluency in Java programming and a track record of writing production-grade code and leading technical implementation for business-critical systems. Strong technical credibility in streaming and event-driven systems, including topics such as partitioning, ordering, stateful processing, delivery semantics, replay, fault tolerance, and platform resilience. Proven experience leading engineering teams, mentoring developers, and driving delivery while maintaining high standards across design, coding, testing, and operational support. Experience working with modern streaming and data technologies such as Kafka, Pulsar, Kinesis, Flink, Spark Structured Streaming, or equivalent platforms, with the judgment to select the right patterns for the problem. Strong understanding of control, governance, and risk management expectations for production data platforms, particularly where resilience, auditability, and data correctness are business-critical. Ability to work across senior stakeholders while staying close to delivery and operational details, helping teams solve difficult technical problems and execute effectively. Some other highly valued skills may include: Experience leading engineering organizations using modern data platforms such as Databricks or equivalent ecosystems for large-scale data and analytics workloads. Working knowledge of cloud-native platform capabilities across compute, storage, orchestration, observability, and security in support of resilient data services. Strong understanding of software engineering lifecycle practices, including CI/CD, platform automation, release controls, and operational governance for critical services. Experience operating in financial services, payments, trading, or similarly regulated environments where non-functional requirements, controls, and recoverability are essential. Ability to communicate complex technical strategy clearly to senior business and technology audiences, building confidence, alignment, and support for change.

Job Description Job Description Job Title: Senior Data Modeler - Integration & Events Location: Washington, DC (On-site) Employment Type: Contract (W2 through ZipStaff - No C2C or 1099) About the Opportunity: ZipStaff is seeking a Senior Data Modeler - Integration & Events to serve as a key technical authority across the Transportation Operations portfolio for a leading transportation organization. In this role, you will define and govern conceptual, logical, and physical data models, shared semantic standards, and event/API contracts to bridge legacy systems (including mainframe) with modern distributed architectures. By standardizing canonical models, managing schema lifecycles, and establishing formal data contracts in Kafka/Confluent environments, you will ensure reliable, interoperable, and scalable data exchange across mission-critical rail and transit operational platforms. This is an on-site role in Washington, DC. What You'll Do: Design, implement, and maintain conceptual, logical, and physical data models for operational data at rest and data in motion across relational, NoSQL, and event-driven systems. Lead the definition, evolution, and governance of standardized event contracts and API schemas using Kafka Schema Registry, enforcing compatibility modes, schema references, and consumer-impact standards. Establish and govern canonical information models, shared operational entities, authoritative definitions, relationships, and naming conventions aligned with enterprise standards (such as ISO/IEC 11179-5). Reverse-engineer and analyze legacy operational systems-including mainframe environments-to support target-state modernization and seamless data integration. Partner with solution architects, application engineers, business SMEs, and data integration teams to maintain end-to-end traceability between business concepts, logical models, physical schemas, and event streams. Review database and schema designs to verify data integrity, normalization tradeoffs, history/effective dating structures, and compliance with enterprise security and governance policies. Facilitate modeling working sessions to translate complex transportation business rules into reusable, consistent technical definitions across systems. Required Qualifications: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical discipline. 8+ years of hands-on data modeling experience designing enterprise conceptual, logical, and physical schemas for mission-critical, highly integrated transactional or operational systems. Proven mastery of data modeling fundamentals, including grain definition, key strategies, normalization/denormalization trade-offs, constraints, temporal/effective dating, and state management across both Relational and NoSQL platforms. Hands-on experience with Kafka and Confluent Schema Registry, with practical knowledge of subjects, schema evolution rules, compatibility modes, and reusable event contracts. Demonstrated track record establishing governed semantic naming standards, metadata dictionaries, and enterprise data models (exposure to ISO/IEC 11179-5 principles preferred). Strong understanding of distributed architectures, middleware, API integration, and hybrid legacy-to-cloud migration patterns (mainframe exposure is a plus). Excellent communication, documentation, and stakeholder facilitation skills. Ability to work on-site in Washington, DC. Preferred Qualifications: Domain experience in transportation, railroad, logistics, transit, aviation, or utilities. Experience reverse-engineering mainframe systems for modernization and data integration. Familiarity with enterprise data governance standards such as ISO/IEC 11179-5. Experience facilitating modeling sessions with business and technical stakeholders in complex operational environments. Benefits: Health Insurance. Dental Insurance. Vision Insurance. 401(k) + 401(k) matching. Paid time off. Referral Program. About ZipStaff: ZipStaff partners with leading organizations to connect skilled technology professionals with high-impact contract opportunities. We focus on quality matches, clear communication, and long-term success for candidates and clients. To apply, submit your resume highlighting your 8+ years of enterprise data modeling experience, hands-on Kafka/Confluent Schema Registry work, and experience designing conceptual, logical, and physical models for operational or transactional systems. Pure research or junior experience will not be considered.

We're partnering with a rapidly growing consumer-facing organization building an internal enterprise AI orchestration platform focused on intelligent support, enterprise knowledge retrieval, workflow automation, and AI-enabled experiences across field operations and corporate teams. This is not a traditional software engineering role centered around a specific language or framework. The team is looking for a strong senior engineer who remains highly hands-on technically, thinks in systems, and uses AI-assisted development tools to accelerate delivery of production-ready software. The environment is highly integration-focused and product-oriented, with an emphasis on building scalable internal platforms and operational tooling rather than isolated AI demos or prototypes. What You'll Be Doing Build AI-enabled internal applications and workflow experiences across desktop and mobile contexts Develop secure API-first integrations across enterprise systems, SaaS platforms, and internal services Design and implement agentic workflows capable of retrieving knowledge, calling tools, and automating operational tasks Work closely with architecture, product, and business stakeholders to translate ambiguous operational challenges into working software Use AI-assisted development tooling such as Cursor, Claude Code, GitHub Copilot, or similar platforms to accelerate engineering delivery Review, validate, and harden AI-generated code for production use Contribute to scalable engineering patterns, integration standards, and platform architecture decisions Build with strong attention to testing, observability, maintainability, and security Required Skills & Experience 4+ years of professional software engineering experience Strong background in application, platform, or full stack engineering Experience building production-grade enterprise applications, integrations, or internal platforms Strong API and systems integration experience Familiarity with API gateway or service gateway platforms such as Kong, Apigee, AWS API Gateway, or similar technologies Experience working directly with business stakeholders and operating in ambiguous environments Hands-on experience using AI-assisted development workflows in real-world software delivery Strong systems thinking and product mindset Experience with CI/CD, automated testing, observability, and secure engineering practices Preferred Experience Agentic AI frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar MCP, tool-calling, or function-calling workflows RAG, vector search, embeddings, or enterprise knowledge retrieval systems AWS Bedrock or enterprise LLM platforms Experience with enterprise automation or orchestration tooling Familiarity with Workato, MuleSoft, Boomi, or similar iPaaS platforms Exposure to retail, restaurant, field operations, or enterprise support environments Experience integrating platforms such as Zendesk, Workday, Teams, Snowflake, Datadog, or similar enterprise systems Mobile application exposure is helpful but not required Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual's skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company's 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products. EEO Notice Vaco by Highspring is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race (including but not limited to traits historically associated with race such as hair texture and hair style), color, sex (includes pregnancy or related conditions), religion or creed, national origin, citizenship, age, disability, status as a veteran, union membership, ethnicity, gender, gender identity, gender expression, sexual orientation, marital status, political affiliation, or any other protected characteristics as required by federal, state or local law. Vaco by Highspring and its parents, affiliates, and subsidiaries are committed to the full inclusion of all qualified individuals. As part of this commitment, Vaco by Highspring and its parents, affiliates, and subsidiaries will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact . Vaco by Highspring also wants all applicants to know their rights that workplace discrimination is illegal. Representation Notice By submitting to this position, you agree that you will be giving Vaco by Highspring the exclusive right to present your as a candidate for the foregoing employment opportunity. You further agree that you have represented information about yourself accurately and have not affirmatively misrepresented your qualifications. You also agree to maintain as confidential, to the fullest extent permitted by law, any information you learn from Vaco by Highspring about the position and you will limit disclosure of information about the position only to the extent necessary to perform any obligations in furtherance of your application. In exchange, Vaco by Highspring agrees to exercise reasonable efforts to represent you through all solicitation, job screening and resume dispersal. For residents of Ontario, Canada: Based on Highspring's discussions with its Client, Highspring's understanding is that this position for employment is a current vacancy (either through Highspring as a contractor or with the client directly). Privacy Notice Vaco by Highspring and its parents, affiliates, and subsidiaries ("we," "our," or "Vaco by Highspring") respects your privacy and are committed to providing transparent notice of our policies. California residents may access Vaco by Highspring HR Notice at Collection for California Applicants and Employees here. Virginia residents may access our state specific policies here. Residents of all other states may access our policies here. Canadian residents may access our policies in English here and in French here. Residents of countries governed by GDPR may access our policies here. Additionally, submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. More details about Vaco by Highspring's use of AI can be found here (). Further assessment of candidates beyond this initial phase will be conducted by recruiters and hiring managers. Vaco by Highspring does not know and cannot opine on if its client's use of AI products in hiring. Pay Transparency Notice Determining compensation for this role (and others) at Vaco by Highspring depends upon a wide array of factors including but not limited to: the individual's skill sets, experience and training; licensure and certification requirements; office location and other geographic considerations; other business and organizational needs. With that said, as required by local law, Vaco by Highspring believes that the following salary range referenced above reasonably estimates the base compensation for an individual hired into this position in geographies that require salary range disclosure. The individual may also be eligible for discretionary bonuses.

The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Datae. You will be at the center of the most consequential shift in enterprise technology: making organizations truly AI-ready. Every agentic AI system, every foundation model grounded in enterprise knowledge, and every GenAI application that moves from prototype to production depends on the data layer beneath it - and that's what you build. You will design and implement modern data platforms (lake, lakehouse, mesh), architect data pipelines that transform raw, fragmented data estates into governed, AI-ready assets; and design and implement enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graph architectures that allow foundation models and AI agents to reason accurately, access data securely, and execute autonomously within regulated environments. You will work hands-on inside customer environments with complex data lineage, regulatory overlays (GxP, HIPAA, CDISC), and legacy systems, and ship production-grade data products that serve multiple downstream consumers, from ML model training to agentic orchestration layers. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using AWS services. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives. This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S. 221100 Key job responsibilities - Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise environments, integrating with legacy systems and existing data governance frameworks - Build data products that serve multiple downstream applications and use cases - from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale - Operate with a high degree of autonomy within fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight - Architect contextual knowledge layers, including ontologies and knowledge graphs leveraging AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with the vocabulary and guardrails to reason accurately and execute autonomously within regulated environments - Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with teams across customer IT, business, and partner organizations - Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures - Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI-native for accelerated scale and pace A day in the life AWS Professional Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You'll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud. About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS- 5+ years of cloud architecture and solution implementation experience - Bachelor's degree, or 7+ years of professional or military experience - 5+ years of experience in data engineering, data architecture, and/or data platform development, with hands-on implementation of production data pipelines - Experience with modern data platform design patterns, including data lakes, lakehouses, data mesh, and zero-ETL patterns and streaming architectures, using services such as Amazon SageMaker Lakehouse, SageMaker Unified Studio, Amazon S3 Tables, Amazon Redshift, and zero-ETL integrations - Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments PREFERRED QUALIFICATIONS- AWS certifications in Data Analytics or Machine Learning Specialty preferred - Hands-on experience with Apache Iceberg, Spark, Databricks, Snowflake, Kafka, or equivalent distributed data processing frameworks - Experience designing and implementing knowledge graph architectures, ontology models, or semantic data layers that support AI/ML and agentic AI systems - Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing data access patterns that support identity and least-priviledge access - Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges and conveying technical concepts to both technical and business audiences. - Proficiency in AI-DLC or equivalent AI-accelerated development methodologies - including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, TX, Houston - 153 800.00 USD annually

Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake Store Support Center Summary of Position (Job Purpose) This is an exciting opportunity to join the Data & Analytics Delivery Organization at Family Dollar, where our enterprise is undergoing a major transformation to become a more data-driven organization. Insights from our rapidly growing data environment are fueling critical decisions that shape our customer experience, operational efficiency, and strategic growth. We are seeking a skilled Business Analyst, Enterprise Data & Analytics who is passionate about building scalable data & BI solutions and lives and breathes data. This role collaborates closely with business partners, subject matter experts and engineers to define goals, translate needs into requirements, and deliver features that power analytics and reporting across the enterprise. You will support teams across Digital Marketing, Merchandising, Data Science, Supply Chain, eCommerce, Finance, and Stores by delivering analytics solutions, metrics, dashboards, and data capabilities. The Business Analyst must be highly collaborative, organized, analytical, and an excellent communicator and problem solver. Principal Duties and Responsibilities Partners with Director and Engineering Managers on the development and execution of enterprise data product strategy. Develops clear requirements across business domains by collaborating with Business, Analytics, and Executive teams. Builds and owns a portfolio of data products-including dashboards, KPIs, semantic data layers, and self-service analytics tools-for internal and external stakeholders. Partners with stakeholders to define the UX requirements and user journeys. Works with Analytics partners to design prototypes for metrics, dashboards, and analytical experiences. Partners with Engineering Managers to manage scrum teams by setting priorities, defining epics and stories, and communicating a clear product vision. Translates complex analyses and ambiguous business needs into simple, actionable requirements and clear presentations. Conducts regular and ad hoc reporting, monitors KPIs, and measures product adoption, performance, and ROI. Builds strong cross-functional relationships to ensure alignment across business and technical teams. Maintains knowledge of industry trends, emerging data technologies, and competitive analytics capabilities to identify product improvements and innovation opportunities. Partners with Data Engineering and Governance to ensure data quality, lineage, definitions, and reliability meet enterprise standards. Drives user research, feedback sessions, and change management efforts to improve product usability and adoption. Creates clear documentation including PRDs, user stories, acceptance criteria, release notes, and user guides. Minimum Requirements/Qualifications Bachelor's degree in Business, Information Technology, Analytics, or related field. 3+ years of experience in product management, data analytics, business intelligence, or related functions. 3+ years of hands-on experience with analytics, data, or visualization tools. Excellent analytical and critical-thinking skills with the ability to build business cases, measure impact, and present results to senior leadership. Strong relationship-building, negotiation, and communication skills with a proven ability to influence without authority. High attention to detail with the ability to manage multiple priorities, collaborate across teams, and operate effectively in a fast-paced, changing environment. Strong proficiency in SQL (BigQuery preferred) and BI tools such as MicroStrategy, Tableau, or Power BI. Exceptional verbal and written communication skills, including executive presentations. Familiarity with Agile methodologies and experience writing epics, user stories, and acceptance criteria. Understanding of data modeling concepts, ETL/ELT pipelines, data quality, and semantic layers is a plus. Experience with data governance, KPI definition, product success metrics, or self-service analytics is a strong advantage. Experience in retail, supply chain, or eCommerce is helpful but not required. This is not to be considered a complete list of job duties, as they may be amended or added to as needed. Projected Salary Range: $91000-$102,250 Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and makes all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 Supply Chain Support Family Dollar

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With more than 1,700+ team members, 1,500+ AI & data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by The Washington Post for six consecutive years and named to the Inc. 5000 list of Fastest-Growing Private Companies in 13 of the past 14 years. Credence is a welcoming environment for those looking to grow and make a meaningful impact. We encourage employees to push boundaries and help solve critical, world-changing federal challenges. Credence has an immediate need for an experienced Senior Google Cloud Platform Looker Developer to support the Defense Automatic Addressing System Digital Business Transformation Reports Modernization team. This hands-on software development role will design, build, integrate, test, deploy, troubleshoot, and sustain enterprise analytics applications using Google Cloud Platform, Looker Enterprise, LookML, and Looker Studio or Looker Studio Pro. The developer will translate functional and technical requirements into production-ready Looker applications, governed semantic models, dashboards, and cloud integrations. The role requires advanced LookML and SQL development, experience with cloud data platforms and APIs, disciplined source-control and deployment practices, and the ability to independently resolve application, data, security, and performance issues. The Senior Developer will also conduct technical reviews, establish reusable development patterns, and mentor other developers. Requirements U.S. citizenship and an active DoD Secret clearance at the time of hire, with the ability to maintain required Government access and suitability. Bachelor's degree in Computer Science, Software Engineering, Information Technology, Information Systems, Data Engineering, or a closely related technical discipline, or an approved equivalent combination of education and experience. At least seven years of experience in business intelligence application development, cloud application development, data engineering, or enterprise reporting development, including at least five years of hands-on development in modern business intelligence platforms. At least three years of hands-on Google Looker Enterprise and LookML development experience, including production semantic models, Explores, dashboards, reusable components, access controls, testing, deployment, and sustainment. Hands-on experience developing Looker Studio or Looker Studio Pro reports, reusable data sources, calculated fields, controls, connectors, and governed sharing configurations. Advanced SQL development and performance-tuning skills using BigQuery and at least one additional enterprise platform such as Amazon Redshift or Oracle. Working knowledge of Google Cloud Platform services used for secure analytics solutions, including BigQuery, Identity and Access Management, Cloud Storage, logging, monitoring, and application integration. Experience integrating reporting applications with data sources, APIs, identity services, and cloud components; experience with Looker APIs, embedded analytics, extensions, JavaScript, or Python is strongly desired. Experience with Git-based version control, code reviews, branching, release management, automated validation, and continuous integration and delivery practices. Strong testing and troubleshooting skills across LookML, SQL, data models, dashboards, permissions, integrations, deployment configurations, and application performance. Experience applying secure coding, role-based access, least-privilege controls, auditing, data-protection, and Section 508 accessibility requirements. Experience leading technical design and code reviews, establishing development standards, mentoring developers, and communicating technical risks and recommendations. Experience working in Scrum, SAFe, or another Agile software delivery environment. Current Security Plus CE or another contract-approved certification meeting DoD 8570 or 8140 IAT Level II requirements. Strong technical writing and communication skills, including the ability to document solution designs, code, configuration, testing, deployment, and operational procedures. Preferred Qualifications Google Cloud Professional Data Engineer, Professional Cloud Developer, Associate Cloud Engineer, or another relevant Google Cloud certification. Experience with data modeling, dimensional modeling, ETL or ELT pipelines, data quality controls, metadata, lineage, and enterprise data governance. Experience modernizing legacy reporting applications and validating data, calculations, security, and performance during platform migrations. Experience supporting DLA, DoD, or another federal agency in a controlled cloud environment; a current Common Access Card is preferred. Work Environment This position supports a collaborative federal delivery team and requires adherence to program security, access, and onsite or hybrid work requirements Salary Range: $150,000 - $190,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Free Food & Snacks Wellness Resources Stock Option Plan

The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Datae. You will be at the center of the most consequential shift in enterprise technology: making organizations truly AI-ready. Every agentic AI system, every foundation model grounded in enterprise knowledge, and every GenAI application that moves from prototype to production depends on the data layer beneath it - and that's what you build. You will design and implement modern data platforms (lake, lakehouse, mesh), architect data pipelines that transform raw, fragmented data estates into governed, AI-ready assets; and design and implement enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graph architectures that allow foundation models and AI agents to reason accurately, access data securely, and execute autonomously within regulated environments. You will work hands-on inside customer environments with complex data lineage, regulatory overlays (GxP, HIPAA, CDISC), and legacy systems, and ship production-grade data products that serve multiple downstream consumers, from ML model training to agentic orchestration layers. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using AWS services. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives. This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S. 221100 Key job responsibilities - Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise environments, integrating with legacy systems and existing data governance frameworks - Build data products that serve multiple downstream applications and use cases - from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale - Operate with a high degree of autonomy within fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight - Architect contextual knowledge layers, including ontologies and knowledge graphs leveraging AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with the vocabulary and guardrails to reason accurately and execute autonomously within regulated environments - Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with teams across customer IT, business, and partner organizations - Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures - Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI-native for accelerated scale and pace A day in the life AWS Professional Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You'll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud. About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship and Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS - 5+ years of cloud architecture and solution implementation experience - Bachelor's degree, or 7+ years of professional or military experience - 5+ years of experience in data engineering, data architecture, and/or data platform development, with hands-on implementation of production data pipelines - Experience with modern data platform design patterns, including data lakes, lakehouses, data mesh, and zero-ETL patterns and streaming architectures, using services such as Amazon SageMaker Lakehouse, SageMaker Unified Studio, Amazon S3 Tables, Amazon Redshift, and zero-ETL integrations - Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments PREFERRED QUALIFICATIONS - AWS certifications in Data Analytics or Machine Learning Specialty preferred - Hands-on experience with Apache Iceberg, Spark, Databricks, Snowflake, Kafka, or equivalent distributed data processing frameworks - Experience designing and implementing knowledge graph architectures, ontology models, or semantic data layers that support AI/ML and agentic AI systems - Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing data access patterns that support identity and least-priviledge access - Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges and conveying technical concepts to both technical and business audiences. - Proficiency in AI-DLC or equivalent AI-accelerated development methodologies - including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, TX, Houston - 153 800.00 USD annually

Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake Store Support Center Summary of Position (Job Purpose) This is an exciting opportunity to join the Data & Analytics Delivery Organization at Family Dollar, where our enterprise is undergoing a major transformation to become a more data-driven organization. Insights from our rapidly growing data environment are fueling critical decisions that shape our customer experience, operational efficiency, and strategic growth. We are seeking a skilled Business Analyst, Enterprise Data & Analytics who is passionate about building scalable data & BI solutions and lives and breathes data. This role collaborates closely with business partners, subject matter experts and engineers to define goals, translate needs into requirements, and deliver features that power analytics and reporting across the enterprise. You will support teams across Digital Marketing, Merchandising, Data Science, Supply Chain, eCommerce, Finance, and Stores by delivering analytics solutions, metrics, dashboards, and data capabilities. The Business Analyst must be highly collaborative, organized, analytical, and an excellent communicator and problem solver. Principal Duties and Responsibilities Partners with Director and Engineering Managers on the development and execution of enterprise data product strategy. Develops clear requirements across business domains by collaborating with Business, Analytics, and Executive teams. Builds and owns a portfolio of data products-including dashboards, KPIs, semantic data layers, and self-service analytics tools-for internal and external stakeholders. Partners with stakeholders to define the UX requirements and user journeys. Works with Analytics partners to design prototypes for metrics, dashboards, and analytical experiences. Partners with Engineering Managers to manage scrum teams by setting priorities, defining epics and stories, and communicating a clear product vision. Translates complex analyses and ambiguous business needs into simple, actionable requirements and clear presentations. Conducts regular and ad hoc reporting, monitors KPIs, and measures product adoption, performance, and ROI. Builds strong cross-functional relationships to ensure alignment across business and technical teams. Maintains knowledge of industry trends, emerging data technologies, and competitive analytics capabilities to identify product improvements and innovation opportunities. Partners with Data Engineering and Governance to ensure data quality, lineage, definitions, and reliability meet enterprise standards. Drives user research, feedback sessions, and change management efforts to improve product usability and adoption. Creates clear documentation including PRDs, user stories, acceptance criteria, release notes, and user guides. Minimum Requirements/Qualifications Bachelor's degree in Business, Information Technology, Analytics, or related field. 3+ years of experience in product management, data analytics, business intelligence, or related functions. 3+ years of hands-on experience with analytics, data, or visualization tools. Excellent analytical and critical-thinking skills with the ability to build business cases, measure impact, and present results to senior leadership. Strong relationship-building, negotiation, and communication skills with a proven ability to influence without authority. High attention to detail with the ability to manage multiple priorities, collaborate across teams, and operate effectively in a fast-paced, changing environment. Strong proficiency in SQL (BigQuery preferred) and BI tools such as MicroStrategy, Tableau, or Power BI. Exceptional verbal and written communication skills, including executive presentations. Familiarity with Agile methodologies and experience writing epics, user stories, and acceptance criteria. Understanding of data modeling concepts, ETL/ELT pipelines, data quality, and semantic layers is a plus. Experience with data governance, KPI definition, product success metrics, or self-service analytics is a strong advantage. Experience in retail, supply chain, or eCommerce is helpful but not required. This is not to be considered a complete list of job duties, as they may be amended or added to as needed. Projected Salary Range: $91000-$102,250 Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and makes all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 Supply Chain Support Family Dollar

This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description Architecture & Platform Strategy Define and evolve the target-state architecture for the self-serve data, AI, and agentic AI platform, aligned to enterprise strategy, data mesh principles, and regulatory requirements Establish enterprise standards and reference architectures for data products, semantic layer services, AI/LLM gateways, agent orchestration, and API- and MCP-based data access Architect the platform layers that let AI systems and agents find, trust, ask, and act on enterprise data - including data product interfaces, semantic context services, and governed write/action patterns Define tiered certification and governance patterns that scale data product trust from registered assets to autonomous-grade, AI-ready products Establish foundational patterns for retrieval, context enrichment, grounding, and tool exposure (RAG, semantic layer, MCP tool surfaces) to support agentic and real-time decisioning use cases Engineering & Infrastructure Lead engineering of scalable, secure platform infrastructure on AWS (S3, Lake Formation, Glue, EKS, Bedrock, IAM, networking) and Databricks (Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, Mosaic AI) Engineer the agentic AI platform stack: agent runtimes, orchestration, agent identity and access management, action/write contracts, evaluation harnesses, and observability Implement platform engineering best practices: infrastructure-as-code (Terraform), CI/CD, automated testing, environment promotion, and GxP/Part 11-compliant change management Drive operational excellence across reliability, cost management (FinOps for data and AI workloads), observability, and incident response, grounded in SRE and Well-Architected practices Ensure security, data protection, and access governance patterns (fine-grained entitlements, row/column-level controls, audit lineage) meet regulated-industry requirements Delivery Leadership & Product Management Contribute to the platform product roadmap: define outcomes, prioritize the backlog, and sequence capability delivery against enterprise AI adoption goals Lead delivery across a team of vendor partners, holding the team to clear standards for quality, velocity, and operability Drive build/buy/adopt decisions with rigor - vendor evaluation, kill criteria, and total-cost analysis - and integrate acquired capabilities into a coherent platform experience Define and track platform health and adoption metrics (DORA, reliability SLOs, self-serve adoption, time-to-data-product) and report progress to senior leadership Serve as a trusted advisor and technical leader: mentor engineers, run architecture reviews, and partner with business domains to identify and enable high-value data and AI use cases Communicate architecture and trade-offs crisply to audiences from engineers to Director/VP. stakeholders, simplifying complexity without losing rigor Basic Qualifications 10+ years in platform engineering, data engineering, or enterprise data/AI platform architecture, including 3+ years leading engineering teams or major platform programs Deep hands-on expertise with AWS data and AI services, including S3, Lake Formation, Glue, EKS, Bedrock, Kinesis/MSK, IAM, and Terraform-based infrastructure automation Strong production experience with Databricks: Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, and workspace/governance administration at enterprise scale Demonstrated experience designing or building agentic AI or LLM-powered systems: agent orchestration, RAG pipelines, LLM gateways, tool/function calling, MCP or comparable protocols, and AI evaluation/observability Proven ability to build resilient, scalable pipelines for high-volume batch and streaming data, with proficiency in SQL and Python (or Scala/Java) Strong understanding of distributed systems, event-driven architecture, workflow orchestration, and API-first integration patterns Experience designing secure, governed, production-grade cloud architectures, including fine-grained access control, lineage, and auditability Track record of delivery leadership: roadmap ownership, backlog management, cross-functional coordination, and shipping platform capabilities that achieve measured adoption Excellent communication skills with the ability to simplify complexity and influence senior decision-makers Preferred Qualifications Experience in biopharma, life sciences, or other heavily regulated domains, with working knowledge of GxP, 21 CFR Part 11, and computer system validation Background in data mesh or federated data architectures, data product operating models, and domain enablement at enterprise scale Experience with semantic layer technologies, knowledge graphs, metadata/catalog platforms, and data contract frameworks Familiarity with FinOps for data and AI workloads, including cost attribution, chargeback/showback, and LLM token economics Experience managing large vendor/partner ecosystems and running structured vendor evaluations with defined success and kill criteria Product management experience or certification; familiarity with DORA metrics, SPACE framework, and platform-as-a-product operating models AWS Professional (Solutions Architect or Data Analytics) and/or Databricks certifications The salary range for this position is: $168,980.00 - $218,680.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans . For additional benefits information, visit: Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans. For jobs in the United States: Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact for assistance. For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster. NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, (c) consistent with the legal duty to furnish information; or (d) otherwise protected by law. . click apply for full job details

Job Description Job Description Company Summary EchoStar is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products. Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV. Our Wireless Technology team is pioneering the future of connectivity. We're developing and enhancing a unique hybrid network model-combining our advanced, cloud-native 5G core with the nationwide reach of our partners. This approach ensures our network is flexible and powerful, designed to satisfy the social, economic, and transformative needs of the changing world. Job Duties and Responsibilities Establish and maintain corporate data model design principles; integrating Kimball and Inmon methodologies with Medallion Lakehouse patterns to deliver performant data assets Architect scalable frameworks and storage tiering to support AI initiatives; including vector databases, Retrieval-Augmented Generation (RAG), and enterprise semantic layers Lead efforts in optimizing query execution, cluster compute, and cloud warehouse costs across enterprise platforms Partner with enterprise architects, data engineering, and business analysis teams to enforce data governance standards and execute data SDLC phases Define data integration solutions and mitigate infrastructure risks to deliver scalable, highly available enterprise data architecture Skills, Experience and Requirements Advanced AI Application expertise; leveraging unstructured data frameworks, vector databases, and Retrieval-Augmented Generation (RAG) within modern data architectures Critical experience in designing multi-tier enterprise data structures, Medallion patterns, and high-performance data lakehouse architectures Strong skills in data modeling, schema design, and versioning within multi-modeler repository environments Critical experience in cloud warehouse cost optimization, cluster compute tuning, and query performance enhancement Expertise in data governance, fine-grained access control (ABAC), data lineage, and compliance standards such as CPNI, CCPA, and SOC2 Exceptional problem solving, collaboration, and cross-functional decision-making capabilities across technical and business stakeholders Additional Qualifications: Preferred industry certifications including Snowflake Certified Architect, Databricks Professional, or AWS Data Engineer Candidates must be willing to participate in at least one in-person interview. Minimum Requirements: Minimum Education: Bachelor's degree in a technical discipline, preferably in Computer Science or Software Engineering, or equivalent combination of education and experience Minimum Experience: 10 years of continuous data architecture and data modeling experience; with at least 3 recent years leading primary data architecture design and implementation in a VLDB / MPP environment Required Technical Skills: 2 years of experience with Azure, AWS, or GCP cloud environments 1 year of experience with Databricks & Genie and/or Snowflake & Cortex 1 year of experience with orchestration tools such as Apache Airflow or Control-M Visa sponsorship not available for this position Benefits We offer meaningful health perks, including flexible spending accounts, HSA, a 401(k) plan with company match, employee stock purchase plan, career opportunities, and a flexible time away plan. Review a benefits summary here: EchoStar Benefits The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies. Compensation is based on the role's location and is subject to change. Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV check. Our company is committed to fostering an inclusive and equitable workplace where every individual has the opportunity to succeed. We are dedicated to providing individuals with criminal or arrest records a fair chance of employment in accordance with local, state, and federal laws. This job posting will be active for a minimum of 3 days and will continue to extend by 3 days until the position is filled. We pride ourselves on developing and promoting talent as an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. EchoStar will accommodate the sincerely held religious beliefs of employees if such accommodations are not undue hardships and are otherwise within the bounds of applicable law. All qualified applicants with arrest or conviction records will be considered for employment in accordance with local, state, and federal law. You may redact any information that identifies age, date of birth, or dates of school/graduation from your application documents before submission and throughout our application process. EchoStar will provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities, unless doing so poses an undue hardship on the Company, poses a direct threat of substantial harm to others, or is otherwise not required by law. EchoStar has a more detailed Accommodation Policy that applies to employees. EchoStar endeavors to make and jobs.accessible to users. Please contact if you would like to discuss the accessibility of our website or need assistance completing the application process. This contact information is for accommodation requests only; do not use this contact information to inquire about the status of applications. If you have questions regarding your application or the recruitment process please email . Click the links to access the following statements: EEO Policy Statement, Pay Transparency, EEOC Know Your Rights (English/Spanish)

Job Description Job Description Company Description Derex Technologies Inc specializes in providing IT consulting, staffing solutions and software services. Globally headquartered in Harrison New Jersey since 1996 Derex delivers the highest quality technology professionals and an array of customized IT talent solutions designed to improve productivity and drive results to global clients throughout North America. With over two decades of unparalleled experience, Derex provides supports to its clientele, across such industries as Systems Integration, Banking and Finance, Telecommunications, Pharmaceutical and Life Sciences, Energy, Healthcare, Technology, Transportation, and local and federal Government agencies. Job Description Title: Microsoft Fabric Data Lead (P&C Preferred) Location: PA (Day 1 Onsite) Overview The Microsoft Fabric Core Lead Engineer is responsible for leading the design, development, implementation, and support of enterprise-scale data and analytics solutions using Microsoft Fabric. The role provides technical leadership, drives architecture decisions, mentors engineering teams, and ensures successful delivery of scalable, secure, and high-performing data platforms. Roles & Responsibilities Technical Leadership Lead the end-to-end implementation of Microsoft Fabric solutions across enterprise programs. Define technical architecture, engineering standards, and best practices for Microsoft Fabric adoption. Provide technical leadership to a team of data engineers and developers. Review solution designs, code, and deployment strategies to ensure quality and scalability. Microsoft Fabric Architecture Design and implement enterprise data platforms using Microsoft Fabric components including OneLake, Lakehouse, Data Warehouse, Data Factory, Real-Time Intelligence, Data Engineering, and Power BI. Architect scalable, cloud-native data solutions supporting analytics, AI, and business intelligence workloads. Establish reusable design patterns and reference architectures. Data Engineering & Integration Design and develop robust ETL/ELT pipelines using Microsoft Fabric Data Factory and Spark Notebooks. Integrate structured, semi-structured, and unstructured data from cloud and on-premises systems. Implement data transformation, cleansing, validation, and orchestration processes. Optimize data ingestion strategies for performance and reliability. Data Modeling & Analytics Design dimensional models, Lakehouse architectures, and enterprise data warehouses. Develop semantic models and datasets for Power BI reporting and self-service analytics. Collaborate with business teams to translate analytical requirements into scalable data solutions. Performance Optimization Optimize Spark workloads, SQL Warehouse performance, and OneLake storage utilization. Implement partitioning, indexing, caching, and workload optimization strategies. Monitor platform performance and proactively resolve bottlenecks. Security & Governance Implement enterprise security using Microsoft Entra ID, RBAC, and Fabric workspace security. Define governance policies for data quality, lineage, cataloging, auditing, and compliance. Ensure adherence to enterprise security, privacy, and regulatory standards. DevOps & Automation Implement CI/CD pipelines using Azure DevOps or GitHub. Automate deployment of Microsoft Fabric artifacts across Development, QA, UAT, and Production environments. Manage source control, release management, and deployment automation. AI & Advanced Analytics Enable AI, Machine Learning, and Copilot capabilities within Microsoft Fabric. Support Data Science workloads using Spark, notebooks, and ML models. Collaborate with AI teams to operationalize predictive analytics and intelligent data solutions. Production Support & Operations Lead production deployments and post-production support activities. Monitor platform health, troubleshoot incidents, and ensure SLA compliance. Implement disaster recovery, backup, and business continuity strategies. Stakeholder Management Collaborate with enterprise architects, product owners, business stakeholders, and cross-functional teams. Participate in architecture review boards and technical governance meetings. Communicate technical solutions and project status to senior leadership. Team Leadership & Mentoring Mentor junior and senior engineers on Microsoft Fabric technologies and engineering best practices. Conduct code reviews, design reviews, and technical knowledge-sharing sessions. Drive continuous improvement initiatives and foster engineering excellence. Required Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field. 10+ years of experience in Data Engineering, Data Warehousing, or Cloud Data Platform development. 4+ years of hands-on experience with Microsoft Azure Data Platform technologies. 2+ years of hands-on experience with Microsoft Fabric in enterprise implementations. Strong expertise in SQL, PySpark, Python, and Spark optimization. Experience with Microsoft Fabric components including OneLake, Lakehouse, Data Warehouse, Data Factory, Power BI, and Real-Time Intelligence. Experience with Azure Data Lake Storage (ADLS), Azure DevOps, GitHub, and CI/CD pipelines. Strong knowledge of dimensional data modeling, ETL/ELT architecture, and data governance. Experience leading technical teams and delivering large-scale enterprise data modernization programs. Preferred Skills Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) Microsoft Azure Data Engineer Associate (DP-203) Experience with Databricks, Synapse Analytics, Azure AI Services, or Microsoft Purview. Knowledge of Agile/Scrum delivery methodologies. Strong communication, stakeholder management, and problem-solving skills. Regards, Manoj Goud Derex Technologies INC Contact : Ext 206 Additional Information All your information will be kept confidential according to EEO guidelines.

Job Description Job Description The Data Architect is responsible for defining and implementing Dal-Tile's enterprise data architecture strategy to support analytics, reporting, data governance, cloud modernization, and AI initiatives. This role partners with business and technology teams to deliver scalable, secure, and trusted data solutions across the enterprise while driving migration from legacy platforms to modern Azure-based technologies. Job Details: This role does NOT provide current or future sponsorship assistance. Please note that we will NOT provide relocation assistance (Candidates are expected to relocate on own 3 weeks from time of offer acceptance). Employees are required to report in office 4 days a week / 7834 CF Hawn Freeway Dallas, Texas 75217 (NO NEGOTIATION). This is a direct hire role; We are NOT open to employing through contractor or agency. Duties and Responsibilities of the Position: Enterprise Data Architecture, BI & Cloud Modernization: Define and maintain Dal-Tile's enterprise data and BI architecture strategy, standards, reference architectures, and roadmaps, including migration of legacy platforms to secure and scalable Azure-based solutions. Establish architecture and delivery standards for dbt, Azure Databricks, Azure Data Factory, Azure Storage, Azure SQL, Power BI, dimensional and semantic models, KPI frameworks, reusable data products, workspace governance, deployment practices, and performance optimization; evaluate Microsoft Fabric where it adds appropriate value. Lead architecture reviews and integration design across the application and data portfolio while documenting architecture decisions, reusable patterns, procedures, quality objectives, and lessons learned. Data Governance, Integration & Business Partnership: Architect and govern data across enterprise applications, SAP platforms, cloud services, APIs, third-party providers, and operational systems by establishing Data Governance, Data Stewardship, Data Observability, Metadata Management, Master Data Management, Data Lineage, privacy, security, and retention practices. Create and maintain architecture diagrams, enterprise and semantic data models, interface designs, end-to-end lineage, technology roadmaps, enterprise KPIs, business metrics, and reporting standards aligned with organizational priorities. Partner with business and technology leaders, Data Engineers, Analytics Engineers, BI specialists, and application teams to resolve cross-functional challenges and deliver governed self-service analytics and trusted data products. AI-Enabled Architecture, Lucid chart AI & Continuous Learning: Define architecture and governance guardrails for responsible use of generative AI, copilots, and agent-based capabilities, including security, privacy, human review, traceability, and lifecycle monitoring. Use Lucid chart AI to accelerate current-state and target-state architecture diagrams, data-flow and lineage visualization, reference-pattern creation, standards validation, and ongoing governance; review and tailor AI-generated outputs to Dal-Tile's approved architecture, security, naming, metadata, and documentation standards before publication. Evaluate AI-assisted capabilities across Power BI, SAP, Azure AI, and related platforms to support governed semantic models, trusted enterprise metrics, AI-ready data products, metadata discovery, redundancy analysis, data observability, and operational automation. Required Experience and Education: Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, or a related discipline, or equivalent experience. 6-8 years of experience in Data Architecture, Enterprise Architecture, Data Engineering, Analytics, or Business Intelligence, including 4-6 years designing enterprise-scale cloud data platforms and analytics solutions. Strong hands-on experience with Azure Data Factory, Azure Databricks, Azure Storage, Azure SQL, Power BI, and dbt for scalable data transformation, testing, documentation, lineage, and deployment practices; Microsoft Fabric experience is a plus. Proven experience leading legacy-to-cloud migration and architecting enterprise environments spanning operational, analytical, SAP, API, and third-party sources. Hands-on experience with SAP ECC and/or SAP S/4HANA data environments and integration with enterprise analytics and reporting platforms. Experience implementing Data Governance, Data Stewardship, Data Observability, Metadata Management, Master Data Management, Data Lineage, privacy, security, and trusted data-product practices. Experience designing enterprise BI and analytics architectures, including dimensional and semantic modeling, KPI frameworks, Power BI governance, workspace administration, deployment pipelines, performance optimization, and self-service analytics. Competencies: Ability to define enterprise reporting strategies and deliver trusted analytical data products supporting executive, operational, and strategic decision-making. Ability to use AI-assisted architecture and documentation tools, including Lucid chart AI, with sound judgment, human validation, version control, and compliance with enterprise governance standards. Excellent communication, presentation, problem-solving, critical-thinking, and stakeholder-management skills, including the ability to translate complex technical concepts into clear business value. Ability to lead cross-functional initiatives, influence standards and practices, manage competing priorities, and provide task-related direction to technical team members. Manufacturing industry experience is highly preferred, with understanding of Supply Chain, Marketing, Customer, Product, Finance, and Operational data domains. Other Pertinent Job Information: Temporary indirect reporting relationships may exist while working as Project lead. May be required to act in senior role, providing task related advice and direction to junior team members. Occasional travel may be required.

Job Description Job Description Who is Fusion Technology? Fusion Technology is a performance-driven HUBZone Small Business concern residing in the heart of the beautiful mountainsides of West Virginia, steps away from the Federal Bureau of Investigation's Criminal Justice Information Services Division's Headquarters. Founded in 2007 by an Engineer-by-trade, Fusion Technology dedicates our valuable resources to providing comprehensive IT services and solutions to mission-critical US Government programs and the Intel Community. Position Location: Springfield, VA Who are you? Security-cleared Professional: An active TS Clearance is required to be considered for this position. Education and Experience: You have a Bachelor's Degree and 10+ years of related experience in data architecting. Other requirements include: Experience with data modeling and architecting using a variety of technologies. Ability to effectively communicate technical information across teams to include bridging technical gaps. Ability to function independently and ability to delegate tasks across teams. Must be able to direct and mentor others on the team. What you'll do: The Data Architect will specialize in data models; staff will support the development, integration, and maintenance of semantic frameworks to enhance data interoperability and knowledge representation across systems. This role involves designing and implementing ontologies, taxonomies, and data models to structure and standardize complex datasets, enabling efficient data sharing and analysis. This position will collaborate with cross-functional teams to align data models with organizational goals. What matters to you matters to us. Fusion Technology values its employees and works hard to ensure proper care for them and their families. We desire to compensate employees in a competitive, motivational, fair, and equitable way with other employers in the marketplace. Salary is only one component of employee compensation but an integral part of recruiting and retaining qualified employees. However, at Fusion Technology, we take a comprehensive approach and consider each employee's needs to tailor a compensation plan that provides financial security and peace of mind. Our competitive package includes a best-in-class matching 401K program, a comprehensive healthcare plan through Cigna, a competitive employer contribution to a health savings account, vision and dental plans, life insurance, short- and long-term disability, and personal leave, in addition to paid certifications and training. Fusion Technology LLC is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills, and experiences within our workforce. Qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law.

Job Description Job Description Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth. We are seeking a Senior Data Architect. This role brings together traditional databases, modern data platforms, and semantic-graph technologies. The ideal candidate leads the design and management of the organizations enterprise data environment, ensuring information is accurate,connected, and ready to support advanced analytics and AI. Responsibilities To maximize data collection and user experience. Analyze and present statistical information using code to create databases and other types of data infrastructure using code to automate data retrieval and storage process Create code strings, run tests, and troubleshoot problems with organization's databases. Required Qualifications Must possess an active Top Secret Clearance Must be willing and able to obtain a polygraph Bachelor's degree with 10+ years of relevant experience, or Master's degree with less than 2 years of relevant experience SQL, MySQL, Hadoop, ETL AWS, Google Cloud Platform, and Python. Fantom Corp is a Software Development, Agile Cloud, Software Development, Cyber Security (Risk Management, Assessments & Authorization (A&A , Data, AI Platform (Computer Vision Models), Podcasting Media Services, and IT Services provider. Established in 2015, Fantom Corp serves Federal customers with top-notch Cybersecurity Architects, Data Scientists/Analysts, Software Engineers/Developers, DevSecOps Engineers, Project Managers, Identity, Credential Access Management (ICAM) services , and Cloud-certified practitioners. We excel in delivering emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML) with a focus on identifying trends, object detection, and classification of structured and unstructured data. Fantom Corp possesses mastery in all aspects of digital audio production. We lead in the ideation and creation of efforts for clients who want to harness the power of podcasting. We guide them in selecting the right show format for their needs and goals. As a Small Business, we possess the innovation, speed and flexibility to meet your requirements. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description WE'RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further. Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients. If this sounds exciting to you, let's chat! Data Architect You own the data spine of the platform: the canonical event envelope, the multi-tenant transactional store, the read-side projections that power every console view and API response, and the AI/ML data infrastructure that makes the system intelligent rather than just instrumented. This is not a specialist role. We are hiring one person who has done all three surfaces at production depth and can hold the trade-offs simultaneously. The data volume is significant, the schema evolution problem is hard, the tenant isolation requirements are unforgiving, and the AI workloads sit on top of all of it. If any of those three surfaces feel uninteresting, this isn't the role. You'll work shoulder-to-shoulder with the Solution Architect on the canonical data model and with the Senior Developer on implementation. You write the migration playbooks, the upcaster chains, the projection rebuild procedures, and the runbooks that let us sleep at night. You will sit in our headquarters in Dallas, TX on a hybrid schedule. The team is in office on Tuesdays, Wednesdays and Thursdays. What experience should you have: 10+ years of data engineering, data platform, or database architecture experience, with at least 3 owning the architecture, not just the implementation. Production experience with event-sourced systems. You have personally implemented or evolved an event envelope, dealt with the upcaster chain problem, and lived with the consequences of an early schema decision. Deep Postgres expertise: schema design, indexing, query plan analysis, RLS. Not "I've used Postgres" but "I know what I'd do differently from the last team." Experience with streaming platforms: Kafka, Redpanda, Pulsar, or Kinesis. You understand the difference between a topic, a partition, a consumer group, and a saga, and you've designed for all of them. Production analytical data infrastructure experience: warehouse design (Snowflake, BigQuery, Databricks, ClickHouse) or modern OLAP patterns. You can take an event log and produce a queryable shape that analysts and AI systems can actually use. Hands-on AI/ML data infrastructure experience: vector databases (pgvector, Pinecone, Weaviate, Qdrant), embedding pipelines, retrieval patterns. You have shipped a RAG system that worked and you know why most of them don't. Strong SQL, strong enough to be the person other engineers go to. Nice to have Drizzle, Prisma, or another modern TypeScript ORM at production depth. Workflow engine experience (Temporal, Cadence, Airflow) and the data implications of long-running processes. Background in feature stores, ML pipelines, or model evaluation infrastructure. Semantic layer experience: dbt, Cube, or Malloy. Compliance experience: SOC 2, HIPAA, GDPR, data residency. The audit story is part of the data story. Open-source work or public writing on data architecture. What you'll be doing in this role: The canonical event envelope and schema evolution strategy: how events are versioned, how upcasters chain, how projections rebuild, and how we add fields without breaking history. You write the rules and enforce them in code review. The transactional data layer: Postgres schema design, tenant isolation via row-level security, indexing strategy, query patterns, and migration discipline. Every table in a data plane carries a tenant_id and a policy. You make sure of that. The read-side architecture: projection design, materialized views, semantic layer for downstream analytics and AI consumption. You decide how we move from event log to queryable shape and how that shape stays cheap to maintain. The AI/ML data infrastructure: vector stores, embedding pipelines, retrieval-augmented generation patterns, feature stores where applicable, and the lineage that lets us trust what comes back. Data governance: lineage, retention, deletion (right-to-be-forgotten in a multi-tenant event-sourced system is a real problem and you'll solve it), and the audit story for every piece of customer data we touch. The operational playbook: projection rebuilds, replay procedures, schema migrations on hot data, vector index maintenance, capacity planning. If the data layer goes sideways at 2am, your runbook is what saves the on-call engineer Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more. Apply today or check out all our opportunities! Applicants must be currently authorized to work in the United States on a full-time basis. The company does not anticipate providing sponsorship for employment visa status (e.g., H-1B, TN, etc.) for this individual position. By submitting your application, you consent to our collection, processing and disclosure of the contained personal data in accordance with our data practices. If you are a resident of the U.S. state of California, you can read about our data practices and your related privacy rights here. If you are a resident of the European Economic Area, Switzerland or the United Kingdom, you can read about our data practices and your related privacy rights here.

Job Description Job Description We are seeking a Principal Data Engineer to lead the architecture, design, and delivery of modern data platforms and analytics solutions for clients. This is a hands-on technical leadership role for someone who can move comfortably between executive-level client conversations, solution architecture, engineering delivery, and mentoring high-performing data teams. The ideal candidate combines deep data-engineering expertise with strong consulting instincts: they can translate business objectives into scalable technical solutions, communicate complex concepts through clear presentations, and guide teams from discovery through implementation and operationalization. Key Responsibilities Lead the end-to-end architecture, design, and delivery of enterprise data engineering, data platform, and analytics solutions for client engagements. Serve as a trusted technical advisor to client stakeholders, including technology leaders, data leaders, architects, and business partners. Facilitate discovery sessions, requirements workshops, technical assessments, architecture reviews, and solution-design discussions. Translate business goals, data challenges, and operating-model requirements into practical data strategies, roadmaps, reference architectures, and implementation plans. Define scalable, secure, reliable, and cost-effective architectures for data ingestion, transformation, storage, governance, orchestration, analytics, and data consumption. Remain hands-on in engineering work, including designing data pipelines, reviewing code, building proof of concepts, resolving complex technical issues, and establishing engineering patterns. Architect and implement batch, real-time, streaming, and event-driven data solutions as appropriate for client needs. Design modern cloud data platforms using technologies such as Snowflake, Databricks, Microsoft Fabric, Azure Data Factory, AWS Glue, Amazon Redshift, BigQuery, or equivalent platforms. Lead the development of robust ETL/ELT pipelines, data models, data APIs, semantic layers, and data products. Establish data engineering standards for code quality, testing, CI/CD, observability, metadata management, data lineage, documentation, security, and production support. Drive adoption of DataOps practices, infrastructure as code, automated testing, deployment pipelines, monitoring, and incident-management processes. Partner with data architects, data scientists, analysts, application architects, security teams, and business stakeholders to ensure solutions are aligned to enterprise architecture and business outcomes. Present technical recommendations, architecture options, delivery status, risks, and strategic roadmaps to both technical and executive audiences. Lead client-facing demonstrations, workshops, steering-committee updates, and technical presentations. Mentor senior, mid-level, and junior data engineers; provide technical coaching, career guidance, design feedback, and hands-on support. Lead and influence cross-functional delivery teams, including onshore/offshore engineers, architects, analysts, and client technical resources. Participate in project estimation, staffing, delivery planning, risk management, solution scoping, and proposal development. Support pre-sales and business-development activities, including solutioning, client presentations, technical discovery, RFP responses, estimates, and statement-of-work development. Stay current on emerging data, cloud, AI, governance, and analytics technologies; evaluate where they provide meaningful business value for clients. Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; equivalent professional experience may be considered. 10+ years of progressive experience in data engineering, data warehousing, data integration, data architecture, or related technical disciplines. 3+ years of experience in a technical leadership, lead engineer, solution architect, staff engineer, principal engineer, or consulting leadership capacity. Demonstrated experience architecting and delivering enterprise-scale data platforms and data integration solutions. Strong hands-on expertise in SQL and at least one modern programming language, preferably Python, Scala, Java, or C#. Strong experience with ETL/ELT design, data pipeline development, data transformation frameworks, orchestration, and workflow automation. Experience with one or more cloud providers: Microsoft Azure, AWS, or Google Cloud Platform. Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies. Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools. Knowledge of distributed data-processing technologies such as Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable platforms. Experience designing both batch and near-real-time or streaming data solutions. Strong understanding of dimensional modeling, data vault, normalized data models, lakehouse architectures, data lake architectures, and data warehouse design principles. Experience implementing data quality, data validation, monitoring, lineage, metadata, governance, and security controls. Working knowledge of DevOps and DataOps practices, including Git-based source control, CI/CD, automated testing, deployment automation, and infrastructure as code. Strong understanding of cloud security principles, identity and access management, encryption, secrets management, and role-based access controls. Proven ability to lead architecture discussions and make well-reasoned technical tradeoffs involving performance, scalability, reliability, maintainability, security, and cost. Excellent verbal, written, and presentation skills, with the ability to explain technical concepts clearly to business stakeholders and executive audiences. Experience in a consulting, professional services, systems integrator, or client-facing delivery environment. Preferred Qualifications Experience designing data platforms that support AI, machine learning, generative AI, retrieval-augmented generation, feature stores, vector databases, or advanced analytics workloads. Certifications in AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, or other relevant data technologies. Experience with master data management, data cataloging, data governance, privacy, regulatory compliance, or data stewardship programs. Experience with tools such as Collibra, Alation, Microsoft Purview, Unity Catalog, Informatica, Monte Carlo, Great Expectations, or similar governance and observability platforms. Experience with Salesforce, SAP, ERP, CRM, finance, supply-chain, healthcare, retail, manufacturing, or other enterprise operational data domains. Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms. Experience with containerization and cloud-native technologies such as Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi. Prior experience contributing to proposals, estimates, statements of work, or technical sales pursuits. Experience managing or leading distributed onshore/offshore delivery teams. Powered by JazzHR zr49e0PRzQ