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Pay Range: $55.00hr - $60.00hr Job Overview: The Senior Solution Architect EHR, Clinical Integration & Automation is responsible for architecting and providing technical leadership for complex enterprise healthcare solutions involving Electronic Health Record (EHR) systems, clinical applications, cloud platforms, data integration, APIs, event-driven architectures, automation technologies, and enterprise applications. This role will lead technical Client and solution architecture from initial business requirements through detailed design, development, testing, deployment, and production stabilization. The Senior Solution Architect will work closely with clinical/EHR application teams, Automation Analysts, Full Stack Developers, Data Engineers, Application Engineers, QA Engineers, infrastructure teams, security teams, and business stakeholders to translate complex clinical and operational requirements into secure, scalable, reliable, and supportable technical solutions. This is a hands-on technical architecture role. The successful candidate must have significant prior experience designing and developing enterprise solutions and must be capable of going beyond conceptual architecture. The architect should be able to evaluate code-level and integration-level designs, analyze data and system interactions, prototype technical approaches when necessary, troubleshoot complex issues, and provide detailed technical direction to engineering teams. The role requires strong experience with modern enterprise technologies including Google Cloud Platform (GCP), .NET, APIs, Kafka/event-driven architectures, data engineering, SQL, CI/CD, and automation/RPA technologies, combined with strong experience integrating with EHR and healthcare technology ecosystems. Required Skills: Data warehouse and lakehouse platforms (Snowflake, Databricks, Synapse, Redshift, BigQuery). ETL/ELT design and pipeline orchestration. Distributed processing (Spark, SQL, Python). Streaming and event-driven architecture (Kafka, Event Hubs, Kinesis). Data integration (APIs, change data capture). Data quality and master data management. DevOps, CI/CD, and infrastructure as code. Analytics and BI enablement (Power BI, semantic layers). AI/ML data pipelines and feature stores. Architecture documentation and design reviews. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.

Overview We are authentic, professional providers of fun, focused on building a Great Place To Work For All by staying true to our mission: "Life's a Party, We're Makin' It Fun!" and "So Much Fun It's Scary!" At Spencer's and Spirit, we do the right thing always-integrity, fairness, respect, and transparency are our foundation. You will find our culture to be inclusive, passionate, resilient, and one that values differences and embraces all. One Team / One Goal We are leaders and owners of our business success. Whether it's developing new and exclusive costumes, quality testing products, or implementing technology solutions, our teams understand the value of working collaboratively to embrace change through innovation, curiosity, and thoughtfulness. We offer a comprehensive benefits package that includes: Flexible work environment Career advancement Competitive base salary Bonus opportunity Vacation, Personal, Sick and Holiday pay Medical, Dental, Vision, Disability, Life and AD&D insurance 401k with a company match 30% merchandise discount Responsibilities The Senior Business Analyst is responsible for providing decision supporting analysis to the organization's executive team. Responsibilities include strategic and operational analysis primarily for the Supply Chain, Marketing & Merchandise Planning departments. Partner with management to develop analysis that supports key merchandise, marketing and supply chain decisions Assess performance against key performance indicators (KPI) and metrics to improve business processes. Interact with key business managers to obtain or create fact-based metrics Develop KPI reporting that is insightful and actionable Interpret and analyze raw data to understand the implications and make recommendations on key business decisions Build and generate analysis, decision-support tools and informative dashboards from a variety of different data sources to provide clear, accurate and timely decision support to management Lead a variety of special projects by providing business expertise through scenario modeling Create and maintain different data assets as well as enforce data quality standards Qualifications Bachelor's degree and three years relevant work experience in a strategic planning, analytical or quantitative disciplined role Expert working knowledge of the Microsoft Office suite to include Excel and PowerPoint Experience with Power BI, Tableau, and DataBricks is desired Experience using generative AI tools such as Copilot, ChatGPT, Databricks Genie to enhance analysis Proven ability to perform strategic analysis, derive insights and communicate findings to stakeholders Experience diagnosing, isolating, and resolving complex issues and recommending and implementing strategies to resolve problems Ability to manage priorities in a fast-paced work environment Ability to multitask and maintain attention to detail Able to work independently as well as in a team The pay range reflects the potential base salary range for this role. Individual base pay is determined by various factors such as relevant experience and skills, and the scope and responsibilities of the position. Pay Range $65,000 - $75,000

Genesis10 is currently seeking a Data Modeler - Hybrid position with a Global Financial Institution located in North Carolina. This is a 6+ month contract opportunity. This role involves designing, implementing, and optimizing data models for a data warehouse. The ideal candidate will work extensively with IBM InfoSphere Data Architect (IDA) to create logical and physical data models for deployment in Azure and Databricks environments, ensuring alignment with business requirements and the organization's data strategy. Responsibilities: Design, implement, and optimize data models for the data warehouse, ensuring alignment with business requirements Translate business requirements into conceptual, logical, and physical data models, ensuring data quality and consistency across systems Participate in data architecture and design discussions to ensure data modeling best practices are followed Develop and maintain documentation of data models, data flow diagrams, and database design specifications Work with stakeholders to ensure the data models support analytics, reporting, and data integration needs Perform impact analysis of changes to existing models and collaborate with teams to assess the effects on downstream systems Continuously improve and optimize data models to enhance performance and data accessibility Requirements: Senior level experience (10+ years) as a Data Modeler Extensive experience with IBM IDA (InfoSphere Data Architect) to create logical and physical data models Experience with implementing and maintaining data models in Azure and Databricks environments Strong understanding of data warehouse concepts and database design principles Ability to collaborate with data engineers and business stakeholders Pay range: Up to $74.11 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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 This Data Platform Engineer will have the unique opportunity to apply cutting-edge data and analytics technologies to one of the most meaningful challenges in healthcare: ensuring the quality of medicines that improve and save lives. As a pivotal member of R&D Quality, this role will help transform how quality insights are generated, scaled, and acted upon across Gilead's drug development and clinical research programs. Through the development of robust data pipelines and advanced analytics platforms, the successful candidate will enable more proactive quality oversight, smarter decision-making, and continuous improvement, ultimately supporting Gilead's mission to deliver life-changing therapies to patients worldwide. The Data Platform Engineer will partner with the Quality Analytics & Insights team, a small, high-impact group responsible for advancing data and analytics capabilities across R&D Quality. This role will build and maintain the data infrastructure that supports Quality Performance and Quality Health analytics focused on signal detection, risk analytics, early identification of emerging issues, mitigation strategies, and continuous improvement. Working closely with analytics professionals, the engineer will transform analytical prototypes into scalable, production-ready solutions through robust data pipelines, cloud infrastructure, monitoring, and automation. The role will collaborate directly with Quality teams, IT, and global delivery teams to support key Quality System elements and programs, including Audit, Deviation, CAPA, Risk Management, Escalation/Serious Breach, and Quality Analytics, while helping define the technology roadmap for next-generation analytics and automation across the organization. Primary Responsibilities Data Engineering Technical Ownership: Operate as a self-directed contributor who scopes, plans, and drives initiatives end-to-end - translating ambiguous Quality problems into technical solutions, making sound architectural trade-offs, and delivering production outcomes with minimal oversight. Infrastructure & Environment Automation: Independently provision and manage cloud infrastructure using infrastructure-as-code and containerization, standing up reproducible, scalable environments for data processing, application deployment, and analytics with minimal reliance on external teams. Application Lifecycle Management: Develop and maintain pipelines to transition analytics applications and data products from development to production, including packaging, CI/CD, automated testing, and deployment. Support reliable delivery of Quality use cases such as signal detection, risk analytics, and Quality Performance/Quality Health analytics. Data Pipeline Development: Design robust batch and streaming data workflows; integrate, define, and manage data sets, lineage, and reuse across QMS data sources (e.g., Audit, Deviation, CAPA, Risk Management). Data Orchestration: Author and schedule reliable, observable workflows using orchestration tools and distributed processing, ensuring dependencies, retries, and SLAs are handled without manual intervention. Production Operations & Monitoring: Ensure the reliability and scalability of data pipelines and analytics applications; implement effective logging, tracing, and alerting. Establish monitoring for data quality, pipeline performance, and service health, paying particular attention to QMS data feeds, where low-frequency quality signals amplify the impact of anomalies. Collaboration & Enablement Cross-functional Partnership: Work closely with analytics professionals, Quality analysts, and stakeholders across R&D Quality programs (e.g., Audit, Deviation, CAPA, Risk Management, Escalation/Serious Breach). Provide frameworks, templates, and guardrails that accelerate analytics delivery. Testing & Validation: Demonstrate a strong focus on testing by setting up frameworks for data pipelines, analytics applications, and production code. Design validation pipelines with automated quality gates, including type checking, linting, integration tests, and contract tests. Documentation & Release Management: Develop clear, detailed guides, operational playbooks, and user instructions. Coordinate releases with IT and the global team; maintain runbooks, rollback strategies, and change tickets. Security & Compliance: Apply security, access-control, and data-governance best practices across pipelines and infrastructure, ensuring solutions meet the expectations of a validated, GxP-regulated environment. Innovation & Technical Strategy Technology Evaluation & Roadmap Input: Evaluate emerging data, cloud, and analytics tooling; prototype promising approaches and recommend adoption, contributing to the technical roadmap for next-generation Quality analytics and automation. Tech Stack Basic Programming & scripting: Python and SQL; scripting with Python, Bash, or PowerShell. Source control: Git and source control management. CI/CD & release management: Working knowledge of CI/CD tools and release management (e.g., GitHub Actions). Cloud platforms: Hands-on experience with a major cloud provider (AWS or Azure). Containers: Container technologies (Docker; Kubernetes). Data platform: Databricks. Preferred Cloud infrastructure / infrastructure-as-code: Terraform; broader cloud engineering experience (AWS preferred). Monitoring & logging: Datadog, Splunk, CloudWatch, or Prometheus. Infrastructure concepts: Understanding of networking, security, and infrastructure fundamentals. Basic Qualifications: Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD / PharmD Preferred Qualifications: Degree in computer science, computer engineering, information systems, or a related discipline with relevant experience in data engineering, platform engineering, or data operations Significant hands-on experience operationalizing data and analytics solutions end-to-end, including data engineering, pipeline development, deployment, and production monitoring. Strong programming skills in key languages such as Python, SQL, Go, and TypeScript, with proven ability to manipulate large and complex datasets using distributed computing technologies. Familiarity with AWS cloud services. Strong troubleshooting and problem-solving skills. Excellent verbal and written communication skills, with the ability to present complex findings to both technical and non-technical audiences and a strong orientation toward teamwork in a fast-paced, regulated environment. Experience building, packaging, and maintaining data processing libraries and analytics applications in production. Experience with CI/CD, infrastructure-as-code, and cloud-based data platforms. Proficiency with Databricks distributed processing (Spark), data orchestration, and similar data and BI technologies. People Leader Accountabilities: Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams. Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current performance and future potential. They ensure employees are receiving feedback and insight needed to grow, develop and realize their purpose. Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem The salary range for this position is: $157,590.00 - $203,940.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location . click apply for full job details

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

Job Description Job Description About the Opportunity Complete Staffing has a client seeking a Data Architect to lead the design and continued evolution of its enterprise data architecture. This is a senior individual-contributor opportunity for an experienced data professional who can bridge data architecture, cloud analytics, SQL Server, data governance, and business intelligence. The ideal candidate will help establish the standards and architecture that data engineers, analysts, and financial reporting teams use to build scalable, secure, and reliable data solutions. The environment includes a modern Microsoft Fabric analytics platform utilizing a Bronze/Silver/Gold medallion architecture, along with a significant on-premises SQL Server environment supporting core transactional workloads. You will help define how data moves from systems such as Dynamics 365 F&O, SQL Server, APIs, and flat files into Microsoft Fabric and OneLake, how it is transformed and modeled, and how it ultimately supports trusted Power BI reporting and analytics. This role offers the opportunity to have significant influence over the organization's long-term data strategy while remaining hands-on with architecture and technology. What You'll Do Enterprise Data Architecture Own and evolve the organization's target-state data architecture across Microsoft Fabric and on-premises SQL Server. Establish architectural standards for determining which workloads should remain on-premises, move to the cloud, or operate in a hybrid model. Define and maintain the organization's Bronze, Silver, and Gold data architecture standards. Design logical and physical data models, dimensional models, and enterprise data structures. Maintain and improve the enterprise data model, business glossary, and data dictionary. Create reference architectures, technical standards, and architecture decision records. Review significant data designs and provide architectural guidance before development begins. Partner with technical and business stakeholders to translate organizational goals into scalable data solutions. Hybrid & On-Premises Data Integration Design integration strategies between SQL Server and Microsoft Fabric. Determine the appropriate integration approach based on data volume, latency, performance, complexity, and cost. Establish strategies for change data capture (CDC), incremental loading, and data watermarking. Design solutions that keep cloud data current while protecting the performance and stability of transactional systems. Partner with database and data engineering teams on high availability, disaster recovery, retention, and archival strategies. Establish standards around SQL Server database design, indexing, partitioning, and performance. Microsoft Fabric Architecture Design Microsoft Fabric tenant, workspace, and capacity architecture. Establish development, testing, and production promotion processes across data, financial analytics, and business reporting environments. Define clear ownership boundaries between IT, FP&A, and business reporting teams. Establish Direct Lake as the preferred Power BI connectivity approach while determining when Import or DirectQuery may be appropriate. Develop standards for source control and deployment using Git and Azure DevOps. Establish best practices for Fabric pipelines, notebooks, semantic models, SQL objects, and other data assets. Monitor platform performance, capacity utilization, and cost, and identify opportunities for optimization. Data Governance, Security & Quality Establish data security standards across the Bronze, Silver, and Gold layers. Partner with security and data governance teams to ensure appropriate access controls and data protection. Support implementation and use of Microsoft Purview for data cataloging, lineage, classification, and governance. Establish data quality and reconciliation standards to ensure reporting data can be traced back to source systems. Help establish standards around promoted and certified Power BI datasets and semantic models. Partner with stakeholders to improve confidence, consistency, and trust in enterprise data. AI & Emerging Data Capabilities Help establish the data foundation needed to support AI, analytics, and agent-based applications. Design structured and unstructured data access patterns for use cases such as Copilot Studio and Retrieval-Augmented Generation (RAG). Evaluate emerging database and data platform capabilities, including vector search, semantic search, and in-database embeddings. Identify practical opportunities where AI and advanced data capabilities can create measurable business value. Collaboration & Mentorship Serve as a technical resource and mentor for data engineers, analysts, and financial reporting teams. Establish and promote strong data modeling and architecture practices. Collaborate with Software Architecture, Infrastructure, Security, Data Governance, FP&A, and business stakeholders. Communicate complex technical concepts clearly to both technical and executive audiences. Provide architectural leadership without requiring direct people management. What We're Looking For Required Qualifications Bachelor's degree in Computer Science, Information Systems, Data Management, or a related field. 5+ years of experience designing and delivering enterprise data solutions. At least 2 years of experience in a data architecture, lead data engineering, or similar senior technical role. Experience designing modern cloud analytics or data platforms. Strong Microsoft Fabric experience preferred; experience with Synapse, Databricks, or comparable lakehouse technologies will also be considered. Strong hands-on experience with SQL Server and T-SQL, including database design, indexing, partitioning, and performance tuning. Strong understanding of dimensional modeling, star schemas, medallion architecture, and ETL/ELT design. Experience integrating on-premises data sources with cloud data platforms. Experience with CDC, incremental loading, and data integration patterns. Working knowledge of Power BI semantic models, DAX, and row-level security. Experience with Python or PySpark for data transformation and large-scale data processing. Experience using Git and Azure DevOps for data and development assets. Strong communication and collaboration skills with the ability to work across technical and business teams. Preferred Qualifications Microsoft certification such as: Microsoft Certified: Fabric Analytics Engineer Microsoft Certified: Fabric Data Engineer Azure Solutions Architect Expert Experience with Dynamics 365 Finance & Operations (F&O) data structures and integrations. Experience with Microsoft Purview. Experience supporting FP&A, financial reporting, or enterprise finance data. Knowledge of General Ledger, cost center, allocation, or similar financial data models. Experience participating in architecture review boards or enterprise technology governance initiatives. Experience in construction, specialty contracting, or another project-based industry. Kansas City metro area resident preferred. This position is not eligible for visa sponsorship.

Job Description Job Description Banyan Software is the best permanent home for software businesses that serve specialized industries, their employees, and their customers. With a buy-grow-and-hold-for-life approach and a permanent capital base, Banyan acquires and grows companies worldwide, honoring founder legacies and helping portfolio companies modernize through shared AI expertise and operational discipline. Founded in 2016, Banyan operates more than 120 portfolio companies across North and South America, Europe, and APAC, and has appeared on the Inc. 5000 list for six consecutive years. The Banyan Software Foundation, endowed with $100 million in Banyan stock, leverages technology to build a greener and more equitable world. The Role We are hiring our first Lead AI Architect to design, build, and run the centralized data and AI platform that powers Banyan. The cornerstone of the work is a centralized data model, a Banyan data lake, that consolidates the data we already have and unlocks safe AI experimentation for our internal functional teams: Finance, M&A, Business Development, and others. This role is modeled on a classical Enterprise Architect role and adapted for an AI-first world. You will set the target-state architecture, choose the patterns we standardize on, write code yourself, and own the result. You will partner with our embedded business analysts and the leaders of each functional vertical so the platform stays grounded in real use cases, not abstractions. This is a player-coach role. You start hands-on. Over time you build and lead a small platform team. What You Will Build A centralized data lake on AWS: the single, governed source of truth for internal Banyan data. Designed for analytics, ML, and AI experimentation. A reference architecture for AI: patterns and building blocks our verticals use to go from idea to safe production: model selection, RAG, evaluation, observability, cost controls. Guardrails that make experimentation safe: data classification, access tiering, sandboxes, audit logging, and clear rules for what can be sent where. A platform team and operating model: the team, standards, and rituals that keep the platform reliable and improving as adoption grows. What You Will Do Define and own the target-state data and AI architecture for Banyan. Make the trade-offs explicit and write them down. Design and build the AWS-centric data lake. Set the patterns for storage, cataloging, query, ingestion, modeling, and lineage. Likely stack: S3, Glue, Lake Formation, Athena, Redshift, Iceberg or similar open table formats, plus Terraform or CDK for infrastructure as code. Stand up the AI experimentation layer: model access via Anthropic, OpenAI and other LLM Establish data contracts, schema standards, naming conventions, and a domain model that holds up as we add sources and acquire companies. Partner with our Senior Business Analysts embedded in Finance, M&A, and Business Development to translate use cases into platform requirements and to unblock their work. Define security, privacy, and AI safety guardrails. Classify data, design access tiering, and set the rules for handling PII, regulated data, and confidential portfolio information. Stay hands-on. Write code, ship infrastructure, run code reviews, and debug production issues. Architects who do not build lose touch. Build the team including vertical aligned Senior Business AI Analysts. Find suitable contractors for data platform engineers, ML platform engineers, and data engineers. Mentor them. Set the bar for engineering quality. Own platform reliability, observability, and cost. Set SLOs, monitor usage, and keep the bill rational as we scale. Represent Banyan's AI and data architecture to our executive team, our portfolio companies, and external partners. First-Year Outcomes A production-ready, governed data lake foundation deployed on AWS, with at least three priority data domains landed and modeled. At least two functional verticals onboarded to the platform with safe, audited data access for analytics and AI experimentation. A documented reference architecture, security model, and standards library that new use cases and new hires can plug into. At least one AI use case running in production through the platform, with monitoring, evaluation, and a clear ROI story. First one to two team hires made and ramped. Who You Are 10+ years building data and AI platforms in production at meaningful scale. You have shipped, not just diagrammed. Deep AWS expertise. Hands-on with S3, IAM, KMS, networking, Glue, Lake Formation, Athena, Redshift, SageMaker, Bedrock, and EKS or ECS. Strong data architecture chops: lakehouse patterns, open table formats (Iceberg, Delta, or Hudi), data modeling, ingestion frameworks (Fivetran, Airbyte, custom), orchestration (Airflow, Dagster, or similar), and lineage. Real experience with modern AI/ML platform patterns: feature stores, model registries, experiment tracking, prompt and evaluation frameworks, retrieval-augmented generation, and basic agentic workflows. A working point of view on AI safety: data classification, PII handling, access tiering, evaluation, and model-risk controls. Hands-on coder. Strong Python and SQL. Comfortable in Terraform or AWS CDK. Reads logs, fixes issues, ships pull requests. Player-coach experience. You have led small teams, mentored engineers, set hiring bars, and grown people. A strong communicator. You can drive an architecture decision review with engineers and explain trade-offs to executives in the same week. Bachelor's degree in computer science, engineering, or a related field. A master's degree is a plus, not a requirement. Bonus Points Experience in private-equity-backed or holding-company environments with multiple business units and inconsistent source systems. Experience designing AI guardrails for non-public, regulated, or competitively sensitive data. Track record of treating internal platforms as products, with named users, SLAs, and a real adoption strategy. Experience with Snowflake or Databricks. Useful when bridging to portfolio company data without forcing a single stack. Past experience as the first or early platform hire at a growth-stage company. Why Banyan Greenfield with real budget. You set the foundation, you do not inherit a tangle. Real ownership of the AI and data architecture for an entire holding company. A long-term horizon. We do not optimize for the next quarter, so the platform you build can compound. A team that treats AI as a serious capability, not a buzzword. We have already built internal AI tooling we use every day. A culture of accountable autonomy. We trust you to do the work. Competitive compensation, benefits, and meaningful long-term upside. Quick Facts Team AI & Data Science Reports to Head of AI (And Or) Head of IT Scope Player-coach. Hands-on architect today, leading a small platform team over time. Location 100% Remote Type Full-time Level Lead Compensation Competitive base of CAD $180,000 to $210,000 plus performance bonus and benefits. Final offer reflects experience and qualifications. How to Apply Send your resume and a short note describing a data or AI platform you have architected. Tell us the choices you made, what shipped to production, and what you would do differently if you were starting over today. We look forward to hearing from you. Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Global Teams, associates, our Operating Companies, and the communities we serve. As a collective, our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance. Please Note: Banyan Software does not accept unsolicited resumes or applications submitted via email, LinkedIn, or other direct channels. All candidates must apply through our official Careers site to be considered for employment. Applications submitted outside of our applicant tracking system will not be reviewed. Recruitment Notice Banyan Software may use artificial intelligence (AI) tools to assist in screening and/or assessing applicants during the recruitment process. All hiring decisions are made by our team. Personal information submitted through your application will be collected and used for recruitment purposes in accordance with applicable privacy laws. Contact us at any time with questions about our process or to request accommodation. Beware of Recruitment Scams We have been made aware of individuals fraudulently posing as members of our Talent Acquisition team and extending fake job offers. These scams may involve requests for personal information or payment for equipment. . click apply for full job details