1723 jobs found

Job Description Job Description As our Manager, Manufacturing Systems, you will lead our Manufacturing Systems team to develop, implement, execute, and support the utilization of manufacturing systems within Zoox's manufacturing operations and Field Service Engineering environment. The three main work scopes of the team are Manufacturing Execution System (MES) and its integration with the Enterprise Resource Planning (ERP), production management and line control systems, and the integration of manufacturing systems from the plant floor to the ERP. You are also responsible for working with other teams within the Manufacturing Engineering organization and cross-functional teams from other Manufacturing Operations Departments, Field Service Engineering, IT and Business Application, and Program Management to formulate short and long-term Manufacturing Systems strategies, including repair traceability and configuration control to support the execution of Zoox requirements. You will work with relevant leaders and teams to develop specific Manufacturing Systems Team roadmaps, project schedules, identify milestones, flag risks, estimate budgets, track costs, and clearly communicate ongoing progress. At Zoox, you will collaborate with a team of world-class engineers and technicians with diverse backgrounds in areas such as automotive and robotics, and you will have the chance to manifest your creativity and provide a high impact on the innovative products at Zoox. In this role, you will: Work with department leaders to translate the top-down corporate strategy and milestones into detailed concepts, roadmaps, timelines, and deliverables that are relevant to the Manufacturing Systems team's activities Develop short and long-term manufacturing and service systems strategies to meet the company's goals Interact with cross-functional leaders to convey Manufacturing systems requirements and work with them to define support resource requirements and tasks to support the achievement of the team's deliverables Represent the Manufacturing and Service Systems team in cross-functional project activities related to the Robot Configuration Management process and execution Collaborate with the IT and Business Applications team to ensure the Manufacturing and Service Systems interact effectively and efficiently with the enterprise-level systems across system planning, development, and execution phases. Manage the Manufacturing and Service Execution Systems Team to design, implement, execute, and standardize manufacturing systems and processes Lead the activities to design, develop, and implement manufacturing systems to enable the manufacturing of advanced components and vehicles, meeting Zoox's and the industry's manufacturing requirements Support day-to-day vehicle and component production operations at Zoox's manufacturing facilities Qualifications Bachelor's degree in a relevant area such as Computer Science or Engineering 15+ years of experience in manufacturing environments utilizing various manufacturing systems, specifically with Manufacturing Execution Systems, SCADA systems, and Line control systems such as PLCs, automation systems, industrial equipment, and integration of these systems in production. Experience in creating long-term and short-term business and technical strategies for implementing manufacturing systems to increase manufacturing efficiency and effectiveness. Strong technical knowledge and experience in Manufacturing Systems architecture, detailed systems functionality, incorporating business requirements into system requirements, overall discrete manufacturing processes, and production order execution. Experience in implementing and executing SAP ME/Mii/PCo, Inductive Automation Ignition SCADA system, Kepware OPC, Siemens PLCs, and industrial automation devices Bonus Qualifications M.S. in Computer Science, Engineering, or a similar field Deep technical knowledge and understanding of SAP ME/Mii/PCo systems and the integration of MES to SAP S4/HANA ERP system modules, specifically PP, PM, EAM, eWM, and QM Significant relevant experience in the automotive industry and/or discrete manufacturing industries, and hands-on experience in a production environment Strong understanding of the architecture and operations of modern manufacturing production lines There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to or your assigned recruiter. A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills. 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 Job Title: AWS Cloud Security Architect Location: Plano, TX/Reston, VA/Columbia, SC/Knoxville, TN/Lafayette, LA/Birmingham, AL Work Model: Onsite - onsite Responsibilities Provide security architecture guidance for enterprise applications, AWS cloud environments, hybrid infrastructure, cybersecurity platforms, APIs, containers, data solutions, and AI enabled applications. Partner with application and engineering teams to securely migrate workloads from on premises environments to AWS and other approved cloud platforms. Define and maintain cloud security patterns, standards, guardrails, security requirements, reference architectures, and implementation guidance. Conduct security architecture reviews, threat modeling, and risk assessments for cloud native, hybrid, API, container, third-party, and AI/GenAI solutions. Define appropriate security controls and recommend remediation or compensating controls when security gaps are identified. Support secure AI/GenAI adoption, including LLM integrations, RAG implementations, prompt security, data protection, access controls, monitoring, logging, and human in the loop safeguards. Support AI governance and risk management processes, including security reviews, monitoring requirements, incident escalation, and lifecycle controls. Assess solutions against applicable security frameworks and standards, including NIST, FedRAMP, and FIPS. Provide security guidance during technology evaluations, architecture reviews, security exceptions, and path to production activities. Work with cybersecurity engineering and operations teams on security capabilities involving SIEM, network security, endpoint security, data protection, and security configuration. Communicate security risks, requirements, and recommendations clearly to both technical teams and business stakeholders. Requirements 8+ years of overall IT experience, including significant cybersecurity and cloud security experience. 5+ years of cybersecurity architecture experience in roles such as Information Security Architect, Cloud Security Architect, or Infrastructure Security Architect. 5+ years of hands-on AWS cloud security experience, including securing enterprise workloads and cloud migrations. Strong knowledge of AWS security services, controls, IAM, networking, logging, monitoring, data protection, and cloud security best practices. Experience securing enterprise cloud and hybrid environments and performing security architecture reviews. Experience with threat modeling, security risk assessments, control gap analysis, and remediation planning. Knowledge of cybersecurity and compliance frameworks such as NIST, FedRAMP, and FIPS. Experience defining and applying security standards, patterns, guardrails, and technical security controls. Working knowledge of AI/GenAI security, including prompt injection, data leakage, model access controls, AI guardrails, observability, approved model usage, and human oversight. Understanding of security considerations for LLMs, RAG solutions, APIs, containers, and enterprise data integrations. Ability to work effectively with application developers, cloud and infrastructure engineers, cybersecurity teams, enterprise architecture, compliance, risk, and business stakeholders. Strong written and verbal communication skills with the ability to explain technical security risks and requirements clearly. Strong organizational, coordination, and stakeholder management skills. CISSP, CCSP, CISA, CISM, GIAC, or similar cybersecurity certification is preferred. AWS Certified Security - Specialty, Azure AZ 500, or another relevant cloud security certification is preferred. Desired Skillset: Security experience across Azure and/or GCP in addition to AWS. AI/GenAI security, AI governance, or AI risk management experience. Container and workload security experience covering build time and runtime controls. API security experience, including enterprise API gateways. Security engineering experience with SIEM, firewalls, endpoint/host security, or security configuration management. Experience with AI-enabled cybersecurity capabilities such as security analysis, vulnerability prioritization, detection support, secure code review, or workflow automation. CISSP, CCSP, CISA, CISM, GIAC, or similar cybersecurity certification. AWS Certified Security - Specialty, Azure Security Engineer Associate (AZ 500), or comparable cloud security certification. Education: Bachelor's degree in Computer Science, Information Systems, or a related field. System One, and its subsidiaries including Joulé 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: Pittsburgh

Job Description Job Description Job Title: Data & AI Solution Architect Duration: Contract to Hire Location: Houston, Texas, United States Work Mode: 5 Days Onsite Position Description Systemone is seeking a Data & AI Solution Architect who blends solution architecture with a product mindset, someone who can lead client workstreams, shape practical architectures, and help build market facing assets that grow pipeline and credibility in Houston. This role is ideal for a high agency consultant who enjoys client facing delivery and practice building: thought leadership, events, offerings, and proposals. Role summary Provides solution architecture development, consultancy and assurance, ensuring applications conform to Shell standards and reference architectures. The role supports a six week GoA JV Audit Data & AI feasibility engagement. Project / business context GoA JV Audit (Data and AI Services): validate feasibility, map the audit process end to end, confirm data/integration readiness, and demonstrate through a working POC that AI enabled capabilities can work with available data before major infrastructure investment. Key responsibilities Develop and assure solution architecture for projects and translate Shell standards into practical designs. Provide technical recommendations, identify new technology opportunities and support reuse of architecture assets. Use Shell architecture tools and reference roadmaps across cloud, integration, mobile, open source and big data. Engage senior business stakeholders and communicate architecture decisions clearly. Key skills / experience Strong stakeholder management and proactive cross team communication. Strong written/verbal communication and ability to tailor content to the audience. Ability to connect business value to technical architecture. Solution evaluation, integration architecture and AI enabled POC architecture. Required Skills: Data Analysis Data Engineering Data Engineering Solutions Architecture Artificial Intelligence Machine Learning Ref: Pittsburgh

Job Description Job Description Snowflake Architect / Data Architect - Houston, TX Location: Houston, Texas (Onsite/Hybrid - Relocation considered) Employment Type: Full-time / Enterprise Data Platform Work Authorization: USC / GC / GC EAD / H4 EAD / L2 ONLY Experience: 8+ years in Data Engineering / Architecture Domain: Oil & Natural Gas Midstream Mandatory + GenAI About The Role We are seeking a Snowflake Architect / Data Architect to design, build, and scale a modern cloud data platform centered on Snowflake and AWS. You will be part of strategic data initiatives building trusted, reusable, governed data products that power analytics, AI, and business intelligence across the enterprise. This is a hands-on architecture + engineering role - not just modeling, but building pipelines, governance, and semantic layers at enterprise scale. This is an excellent opportunity for a hands-on Data Architect who understands that data engineering is not only about moving data, but about making data trusted, discoverable, governed, and meaningful. Key Responsibilities Design, build, and maintain scalable data pipelines across structured, semi-structured, and unstructured data sources Develop data ingestion and ELT processes using Informatica, aligning with enterprise standards Build transformation logic using dbt - modular models, testing, documentation, deployment workflows Design and manage data structures in Snowflake as the central strategic data platform - modeling, performance optimization, security, access controls Work with AWS data services: S3, Glue, Lambda, Athena, EMR, Redshift and cloud-based architectures Support data architecture using Iceberg managed tables - open table formats, interoperability, cataloging, governed access patterns Use Snowflake Catalog and Snowflake Horizon for metadata management, data discovery, governance, lineage, policy enforcement, trusted sharing Collaborate with data architects, governance teams, analysts, application teams, business stakeholders to define trusted data products Work with domain experts to understand business concepts, entities, relationships, terminology in Oil & Gas Midstream domain Support ontology-driven modeling: entity definitions, taxonomies, relationships, business glossaries, semantic mappings Translate business/domain concepts into logical data models, physical models, and reusable data products Implement data quality checks, validation rules, lineage, observability, and governance controls Support data products for analytics and AI-enabled use cases (e.g., asset intelligence, news intelligence) Ensure solutions meet enterprise requirements for security, privacy, access control, performance, reliability Must-Have Qualifications - Please Do Not Apply Without These Strong Snowflake Data Architecture experience - Data modeling, data warehouse/lakehouse design, performance optimization, security, access controls, enterprise-scale implementations Data Governance & Metadata Management expertise - Hands-on with data cataloging, metadata management, data lineage, data quality, governance frameworks, policy-driven access Understanding of Ontology & Semantic Modeling - taxonomies, business glossaries, semantic mappings, RDF/OWL/SHACL/SPARQL, knowledge graphs Working knowledge of AWS services: S3, Glue, Lambda, Athena, EMR, Redshift and cloud architectures Oil & Natural Gas Midstream domain experience (Mandatory) - pipeline, transportation, storage, LNG, natural gas, midstream operations data Claude AI / Generative AI experience (Mandatory) - Claude, LLM-based solutions, AI-ready data platforms, RAG architectures, GenAI implementations Stable work history - No job hoppers (consistent 2-4 year or 4+ year tenures preferred) Nice to Have / Preferred Experience with Snowflake Catalog and Snowflake Horizon Experience building governed data products for analytics, AI, or applications Enterprise governance tooling, especially Informatica governance RDF, OWL, SHACL, SPARQL, graph databases, knowledge graph platforms Semantic layers, business glossaries, metadata models, domain ontologies CI/CD, Git, automated testing, deployment workflows for data pipelines Data observability, lineage tracking, data contracts, data quality frameworks Technical Stack Snowflake AWS (S3, Glue, Lambda, Athena, EMR, Redshift) Iceberg Snowflake Catalog & Horizon Informatica dbt SQL Python Data Governance Ontology & Semantic Modeling Claude AI / GenAI / RAG Screening Questions for Candidates 1. What is your work authorization / visa status? (USC/GC/GCEAD/H4EAD/L2 only) 2. Do you have direct professional experience with Claude AI or LLM-based solutions in production? 3. Do you have working knowledge of AWS services including S3, Glue, Lambda, Athena, EMR, Redshift? (Yes/No) 4. Rate your Snowflake security and access controls experience: No experience / Basic RBAC / Hands-on enterprise policies / Expert-level design 5. Rate your data lineage and data quality management experience 6. Rate your GenAI and RAG architecture experience 7. Describe your tenure history - multiple 8. Describe your Oil & Gas Midstream domain experience - pipeline, transportation, storage, LNG? 9. Describe your Ontology & Semantic Modeling experience 10. Are you currently in Houston, TX or open to relocation?

Job Description Job Description Must send LinkedIn Must send Day/MOnth birth Must send Visa copy Must send Driver's license. Job Title: Data Architect Job id: F/P SDA 123-GEM is updated with all the details Visa Restriction: usc.gc Location: Arlington, TX (Local only) Pay rate: $57 c2c Work Arrangement: Hybrid - Onsite twice a week Job Description We are seeking an experienced Data Mapping Architect with strong expertise in data architecture, data warehousing, Databricks, SQL, and requirements gathering. This role focuses on analyzing existing data products, mapping business requirements to new source systems, and supporting the development of data solutions on the Analytics Platform. The ideal candidate will have extensive experience in enterprise data architecture, source-to-target data mapping, stakeholder management, and technical collaboration with business users and data engineering teams. Key Responsibilities Analyze existing data products and understand current data usage and requirements. Work with Exadata business users to identify the tables, fields, and technical requirements needed for existing data products. Collaborate with the Helix source team to map required business columns to the new source system. Prepare and maintain Source-to-Target Mapping documents. Guide junior team members in developing Source-to-Target Mapping documentation. Provide technical guidance to developers on data design, source integration, and target table development. Ensure target tables on the Analytics Platform align with business requirements. Facilitate technical discussions among source system teams, data engineers, and business stakeholders. Gather and translate business and technical requirements into data mapping and design specifications. Support data architecture and data warehousing initiatives through technical analysis and stakeholder collaboration. Required Skills and Qualifications 10+ years of experience in data mapping or closely related data architecture and data warehousing roles. Strong expertise in Source-to-Target Data Mapping. Extensive experience in Data Architecture and Data Warehousing. Deep proficiency in Databricks. Strong SQL skills and experience analyzing enterprise data structures. Experience gathering and documenting business and technical requirements. Experience working with business users, data engineers, developers, and source system teams. Strong stakeholder management and technical communication skills. Proven experience guiding teams and resolving data design questions. A seasoned Data Architect with strong data expertise who can lead data analysis, source-to-target mapping, requirements gathering, and technical coordination across business and engineering teams.

Job Description Job Description Job Description Role: Snowflake Architect or Data Architect - Domain : Information technology (IT) Job Type : Full Time Location : Houston Experience : 12 - 18 Years Role Summary: We are looking for a Data Engineer to help design, build, and scale a modern cloud data platform centered on Snowflake and AWS. The ideal candidate has strong data engineering fundamentals, experience with enterprise data platforms, and the ability to work with ontologies, semantic models, metadata, and governed data products. Key Responsibilities: Design, build, and maintain scalable data pipelines across structured, semi-structured, and unstructured data sources. Develop data ingestion and extract-load processes using Informatica, aligning with enterprise standards and existing in-house capabilities. Build transformation logic using dbt, including modular models, testing, documentation, and deployment workflows. Design and manage data structures in Snowflake, with Snowflake positioned as the central strategic data platform. Work with AWS-based data services and infrastructure, supporting applications and data products running in the organization's AWS environment. Support data architecture using Iceberg managed tables, including open table formats, interoperability, cataloging, and governed access patterns. Use Snowflake Catalog and Snowflake Horizon to support metadata management, data discovery, governance, lineage, policy enforcement, and trusted data sharing. Collaborate with data architects, governance teams, analysts, application teams, and business stakeholders to define trusted data products. Work with domain experts to understand business concepts, entities, relationships, and terminology. Support ontology-driven modeling, including entity definitions, taxonomies, relationships, business glossaries, and semantic mappings. Translate business and domain concepts into logical data models, physical data models, and reusable data products. Implement data quality checks, validation rules, lineage, observability, and governance controls. Support data products and applications such as news intelligence, asset intelligence, analytics, and AI-enabled use cases. Ensure data solutions meet enterprise requirements for security, privacy, access control, performance, and reliability. Must-Have Requirements: Strong Snowflake Data Architecture experience - Data modeling, data warehouse/lakehouse design, performance optimization, security, access controls, and enterprise-scale Snowflake implementations. Data Governance & Metadata Management expertise - Hands-on experience with data cataloging, metadata management, data lineage, data quality, governance frameworks, and policy-driven data access. Understanding of Ontology & Semantic Modeling. Working knowledge of AWS services such as S3, Glue, Lambda, Athena, EMR, Redshift, and cloud-based data architectures. Oil & Natural Gas Midstream domain experience (Mandatory) - Experience supporting pipeline, transportation, storage, LNG, natural gas, or other midstream operations and data environments. Claude AI / Generative AI experience (Mandatory) - Experience working with Claude, LLM-based solutions, AI-ready data platforms, RAG architectures, or GenAI implementations.

Job Description Job Description Tesorio is the cash flow performance platform, which Accounts Receivable, Treasury, and FP&A teams use to manage, predict, and collect cash. Its AI processes over $30 billion in transactions each year for companies ranging from 50 to 10,000 employees. Series A company Founded: 2013 Funding: $16.9M Visa: Will transfer H1 Salary: $0 - $200k Job required skills: Cloud, NoSQL, SQL, SaaS, Python, Django Responsibilities Responsible for designing & implementing data architecture that will help with scalability, performance & reliability. You will own the data architecture at our company and work closely with the CTO & Engineering Leadership in order to solve the toughest technical challenges You will be a key member of the Engineering Leadership and help set the technical direction at our company Provide coaching & mentorship across the entire engineering organization Architect & implement production-grade code that is reliable, maintainable & scalable Anticipate technical challenges that we will face as we scale About you You've previously worked at startups and have helped them scale You're excited to lead data architecture at a startup You like to design & architect solutions that are reliable, maintainable & scalable You enjoy writing production-grade code to help implement your solutions You have strong opinions, but you hold them loosely You're always learning You love building and shipping magical products that will help thousands of companies The Ideal Candidate 10+ years of experience as a software engineer Prior experience as a Staff Software Engineer or a more senior engineering role Expert at data architecture. From schema design, data storage technologies, debugging data problems, building scalable data solutions & more. You're intimately familiar with the technology problems startups face as they scale because you've worked at a startup before and helped them scale Experience working on large multi-tenant SaaS systems Expertise working on cloud platforms (e.g. AWS) and building large-scale data architectures leveraging their technologies Nice to have Expertise with Python & Python web frameworks (e.g. Django, Flask) Experience working with financial data or working at a fintech company Expertise with AWS

Job Description Job Description Data Architect / Data Engineering Lead Role Overview Seeking a senior Data Architect / Data Engineering Lead to establish enterprise data architectures and lead implementation of scalable data platforms supporting analytics, operational workloads, AI, and machine learning. Key Responsibilities Develop enterprise data architecture and target-state roadmaps. Design data lake, lakehouse, warehouse, operational and analytics platforms. Develop logical and physical data models. Architect batch and real-time data pipelines. Establish data integration and interoperability patterns. Lead ETL/ELT architecture and development. Establish data quality, lineage, metadata, governance, and master-data practices. Design data architectures supporting AI/ML and GenAI. Optimize data performance, scalability, availability, and cost. Work with security teams to protect sensitive data. Lead data engineers and provide technical direction. Support migration and modernization of legacy data environments. Mandatory Qualifications 10 years of data technology experience. 5 years in Data Architect or senior Data Engineering roles. Advanced SQL. ETL/ELT and data integration. Data warehouse/lake/lakehouse architectures. Cloud data platform experience. Data modeling and governance. Experience designing enterprise-scale pipelines. Highly Preferred Azure Data Factory. Azure Synapse. Microsoft Fabric. Databricks. Snowflake. Spark/PySpark. Kafka/event streaming. Purview. Power BI. AI/ML data architecture.

Job Description Job Description Title: DMZ Network Architect Location: Plano, Tx Position Type : FullTime Compensation Pay Range:$165,000 Per Year Description This role involves defining and implementing architectural visions for complex network environments. Located in Plano, TX, this full-time position requires expertise in cloud environments and network security. The architect will work with various stakeholders to ensure solutions are robust and adaptable to evolving requirements. Key Responsibilities Develop the architecture roadmap for technology domains in support of product strategies. Create and evolve solutions based on emerging business needs, ensuring flexibility and modularity. Lead discussions and design complex architectures, finding innovative solutions through experiments and POCs. Assist development teams with system design and provide solutions to architectural challenges. Review designs to ensure nonfunctional requirements like security and scalability are met. Qualifications 10 years of experience in the technology domain with cloud integration expertise. Strong understanding of network security and traffic segmentation. Proficient in routing, switching, and various network protocols. Experience with large-scale network environments and authentication mechanisms. Familiarity with scripting languages and automation tools. Core Technologies Cloud Platforms Network Security Tools Routing Protocols Scripting Languages Automation Tools Contact Authorization: By applying for this job, you agree to receive AI-generated calls, text messages, and/or emails from Mitchell Martin Inc and its affiliates and contracted partners at various frequency through traditional and automated methods. Message and data rates may apply for texts. Carriers are not liable for delayed or undelivered messages. You can access our privacy policy here -policy Benefits: Learn more about our benefits offerings here -perks Onboarding Expectations: Learn more about our Onboarding Process here EEO Statement: Learn more about our EEO policy here -statement

Job Description Job Description Interviews: two internal rounds, one customer Experience: Minimum 12 years Job Description: About the Role We are looking for a Principal AI & Data Architect to define and lead our enterprise data and AI architecture. You will design a Snowflake-centric data platform with a strong semantic layer, and build the foundations for agentic AI systems that reason over trusted, governed enterprise data. You will be a hands-on technical leader, partnering with business, engineering, and security teams to turn data into reliable, AI-ready products. Key Responsibilities Data Architecture & Snowflake Platform Own the end-to-end architecture of the Snowflake Data Cloud: ingestion, storage, transformation, serving, and consumption. Design scalable, cost-efficient solutions using Snowflake features such as Snowpipe, Streams & Tasks, Dynamic Tables, Snowpark, Iceberg tables, Secure Data Sharing, and Marketplace. Define standards for performance tuning, warehouse sizing, clustering, and FinOps/cost governance. Lead modernization and migration from legacy platforms (Teradata, Oracle, Hadoop, SQL Server) to Snowflake. Semantic & Data Modeling Architect enterprise semantic layers, including business metrics, dimensions, hierarchies, and entity relationships. Design dimensional (Kimball), Data Vault 2.0, and canonical/domain models, and map them to the semantic layer. Implement Snowflake Semantic Views and Cortex Analyst semantic models, and integrate with tools like dbt Semantic Layer/MetricFlow, AtScale, Cube, or LookML. Establish ontologies, knowledge graphs, and business glossaries to ensure consistent meaning across the enterprise. Own metadata, lineage, and data contracts across domains (data mesh / data product approach). Agentic AI & GenAI Architecture Design agentic AI architectures: multi-agent orchestration, tool use, planning, memory, and guardrails. Build solutions on Snowflake Cortex (Cortex Agents, Cortex Analyst, Cortex Search, AI functions) and integrate with LLMs and frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, or CrewAI. Implement RAG and text-to-SQL patterns grounded in the semantic layer for accurate, explainable answers. Leverage MCP (Model Context Protocol) and API/tool integrations to expose governed data and actions to agents. Define LLMOps/AgentOps practices: evaluation, observability, prompt/version management, human-in-the-loop, and cost control. Establish Responsible AI practices covering bias, hallucination, privacy, and auditability. Governance, Security & Leadership Implement RBAC, row/column-level security, dynamic masking, tagging, and compliance controls (GDPR, HIPAA, SOC 2, PCI). Partner with data governance on quality, stewardship, and master data management. Provide architectural guidance, design reviews, and mentorship to data engineers, ML engineers, and analysts. Influence executive stakeholders; translate business needs into roadmaps and ROI-backed proposals. Evaluate emerging technologies and produce reference architectures, POCs, and best practices. Required Qualifications 12 years in data engineering, data architecture, or analytics, with 5 years in architect-level roles. 3 years of hands-on Snowflake architecture at enterprise scale (SnowPro Advanced: Architect preferred). Deep expertise in data modeling (3NF, dimensional, Data Vault) and semantic layer design. Proven delivery of GenAI/agentic AI solutions in production (RAG, tool-calling agents, multi-agent workflows). Strong SQL and Python; experience with dbt, Airflow/Dagster, Kafka, and CI/CD (Git, Terraform). Experience on at least one major cloud (AWS, Azure, or GCP). Solid understanding of data governance, security, and privacy frameworks. Excellent communication, stakeholder management, and leadership skills. Preferred Qualifications SnowPro Advanced certifications (Architect, Data Engineer, Data Scientist) and cloud architect certifications. Experience with knowledge graphs/ontologies (RDF/OWL, Neo4j) and graph-RAG. Experience with vector databases and embedding strategies. Background in MLOps and feature stores. Industry experience in BFSI / Healthcare / Retail / Manufacturing . Contributions to architecture blogs, talks, or open-source.

Job Description Job Description Job Description Must Have Technical/Functional Skills • Balor's degree or higher • 12 years of experience in enterprise architecture with a focus on cloud data platforms • Experience in handling multi-cloud platforms (either AWS/Azure, having experience on both will be good). • Hands-on experience in architecture design, solution expertise and implementations. • 5 Years of hand-on experience working on AWS Data and Analytics tool stack (S3, Glue, Athena, Lake Formation, EMR, Redshift, Kinesis, Open Search and others) or Databricks to build repeatable and reusable frameworks for building Data and AI Solutions • Experience with SaaS data platforms - Databricks/Snowflake on AWS • Exposure in monitoring and optimizing cloud cost, governance and security • 5 years of experience designing and implementing scalable computing infrastructure for data solutions, including cloud architectures (AWS, Azure, Google Cloud). • 5 Years of Experience in Data Warehouses, Data Lakes and Data Modelling techniques using Erwin • 5 years of experience with data engineering and data pipelines for on-prem cloud, hybrid data models and data warehouses. • 5 Years of coding experience with Python, Spark, R, SQL or other equivalent programming languages etc • 3 Years of experience implementing Data quality and observability solutions across the enterprise

Job Description Job Description Immediate need for a talented Data Architect. This is a 12+months contract opportunity with long-term potential and is located in Columbus, IN (Onsite) . Please review the job description below and contact me ASAP if you are interested. Job ID:26-33600 Pay Range: $65 - $70/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location). Key Responsibilities: Work Focus: 70%: Data Architecture, AI Governance, AI Agents, and Computer Vision 30%: DevOps, SecOps, and production deployment Data Architecture and Governance - 35% Define and implement enterprise data integration and storage strategies. Design scalable architectures for databases, data lakes, APIs, and analytics platforms. Develop physical, logical, and metadata models. Establish data quality, accuracy, ownership, lineage, retention, and access-control standards. Define governance metrics and monitor alignment with enterprise data strategies. Lead data migration, transformation, validation, and modernization activities. Align solution architecture with central enterprise architecture standards. Design and implement microservices and reusable data services. Monitor and optimize database performance, scalability, availability, and cost. Support analytics, reporting, and data-lake integration. AI Governance, AI Agents, and Knowledge Solutions - 25% Develop a strategy for making trusted enterprise data available to AI applications and agents. Define AI governance standards covering security, privacy, traceability, model risk, human oversight, and responsible AI. Identify and prioritize knowledge-based AI and agentic AI use cases. Design knowledge repositories, semantic search, vector databases, and retrieval-augmented generation solutions. Develop AI solutions from proof of concept through production readiness. Create reusable frameworks for subject-matter-expert agents and enterprise knowledge assistants. Establish long-term support, ownership, lifecycle, and sustainability plans for AI solutions. Define AI performance, accuracy, adoption, cost, and business-value metrics. Implement monitoring for model quality, data drift, hallucination risk, and solution reliability. Computer Vision - 10% Design and implement computer vision solutions for image and video analysis. Develop pipelines for image ingestion, annotation, preprocessing, model training, inference, and monitoring. Support use cases such as object detection, classification, OCR, defect identification, visual inspection, and document-image processing. Evaluate computer vision models and services based on accuracy, latency, scalability, explainability, and cost. Establish governance standards for image data, labeling quality, model validation, privacy, and retention. Deploy computer vision solutions using cloud, edge, or hybrid architectures. Transition computer vision prototypes into reliable production applications. DevOps and SecOps - 30% Establish software development, coding, documentation, testing, and code-review standards. Design and optimize CI/CD and DevSecOps pipelines. Automate application, infrastructure, database, and AI-model deployments. Integrate static code analysis, dependency scanning, container scanning, secret detection, and vulnerability management. Define encryption, identity, access-control, auditing, logging, and sensitive-data handling requirements. Ensure compliance with enterprise cybersecurity and regulatory requirements. Support containerized and microservices-based deployments. Implement monitoring, alerting, incident response, backup, recovery, and operational-support processes. Troubleshoot production issues and drive root-cause analysis and corrective actions. Develop implementation roadmaps in coordination with technical and business leadership. Key Requirements and Technology Experience: Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Systems, Electrical Engineering, or a related technical field. Seven or more years of experience in data engineering, software development, cloud architecture, AI/ML, or related areas. Three or more years of experience designing enterprise data or solution architectures. Hands-on experience with AWS cloud services and cloud-native solution development. Strong experience with relational databases, NoSQL databases, data lakes, and data warehouses. Experience developing data integration pipelines using ETL/ELT, APIs, messaging, or event-driven architectures. Strong knowledge of data modeling, metadata management, data lineage, data quality, and governance. Experience developing or deploying AI, machine learning, generative AI, or knowledge-based solutions. Working knowledge of computer vision concepts and image-processing workflows. Experience implementing CI/CD pipelines and DevSecOps controls. Strong understanding of encryption, identity management, access controls, audit logging, and secure handling of sensitive data. Proficiency in Python and SQL. Experience with Git-based development, automated testing, and code-review practices. Ability to translate business requirements into scalable technical solutions. Strong communication skills with the ability to work across architecture, cybersecurity, engineering, IT, and business teams. Cloud: AWS, including services for compute, storage, databases, security, monitoring, and AI/ML Programming: Python, SQL, scripting, and API development Data Platforms: Relational databases, NoSQL, data lakes, data warehouses, and vector databases Data Integration: ETL/ELT, REST APIs, event streaming, messaging, and microservices AI: Generative AI, AI agents, RAG, prompt orchestration, embeddings, model evaluation, and responsible AI controls Computer Vision: OpenCV, image preprocessing, classification, object detection, OCR, model evaluation, and inference pipelines DevOps: Git, automated testing, CI/CD, infrastructure as code, release management, and environment management Containers: Docker and Kubernetes or equivalent container platforms Security: Secure coding, vulnerability scanning, secrets management, IAM, encryption, audit logging, and compliance Monitoring: Application, database, pipeline, infrastructure, and AI-model observability Our client is a leading IT Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration. Pyramid Consulting, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, colour, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. By applying to our jobs you agree to receive calls, AI-generated calls, text messages, or emails from Pyramid Consulting, Inc. and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy here.

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 Job Description Job ID: 114700-1 Job Title: Systems Engineer (Kubernetes & Application Deployment) Work Location: Irving, TX- ONSITE Work Model: Onsite Duration: 6 Months with possible extension Pay rate: $50-$55/hr on W2/C2C (All inclusive) About the Role We are seeking a highly skilled Systems Engineer to lead the architecture, design, and execution of our application deployment strategies. In this role, you will be the cornerstone of our containerized infrastructure, primarily focusing on Kubernetes. You will partner closely with software engineering, DevOps, and security teams to design robust deployment pipelines, ensure maximum high availability, and build scalable infrastructure that supports our core products. The ideal candidate does not just maintain systems; they actively design deployment topologies, champion GitOps methodologies, and solve complex distributed system challenges. Key Responsibilities Application Deployment Architecture Design Deployment Strategies: Architect and implement scalable, secure, and highly available deployment topologies for microservices and monolithic applications. Pipeline Engineering: Build and maintain advanced CI/CD pipelines incorporating blue-green, canary, and rolling deployment strategies. GitOps Implementation: Drive GitOps practices using tools like ArgoCD or Flux to ensure infrastructure and deployment states are version-controlled and automated. Containerization Optimization: Guide development teams on Dockerfile best practices, multi-stage builds, and container image security/slimming. Kubernetes Ecosystem Management Cluster Lifecycle: Provision, upgrade, and manage production-grade Kubernetes clusters (e.g., EKS, GKE, AKS, or bare metal). K8s Configuration: Develop and maintain Helm charts, Kustomize manifests, and custom resource definitions (CRDs) for complex application requirements. Traffic & Networking: Architect ingress controllers, service meshes (e.g., Istio, Linkerd), and network policies to ensure secure and efficient internal and external traffic routing. Storage & Stateful Loads: Design and manage persistent volumes and stateful sets for applications requiring durable storage. Infrastructure & Reliability Infrastructure as Code (IaC): Automate the provisioning of underlying cloud resources using Terraform, Pulumi, or Ansible. Observability: Implement comprehensive monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana, ELK stack, Datadog, OpenTelemetry) to track deployment health and application performance. Incident Response: Serve as an escalation point for complex deployment failures or cluster degradation, participating in on-call rotations and blameless post-mortems. Required Qualifications Experience: 4+ years of experience in Systems Engineering, DevOps, or Platform Engineering, with at least 2 years in a heavily containerized environment. Kubernetes Mastery: Deep, hands-on experience managing production Kubernetes environments, including cluster scaling, RBAC, network plugins (CNI), and storage (CSI). Deployment Tooling: Proven track record of designing complex deployments using Helm and GitOps controllers (ArgoCD/Flux). Cloud Proficiency: Strong experience with at least one major cloud provider (AWS, GCP, or Azure) and their managed Kubernetes offerings. Scripting & Automation: Proficiency in at least one programming or scripting language (Python, Go, or Bash) for automation and tooling. OS & Networking: Strong grasp of Linux system administration, TCP/IP networking, DNS, and load balancing principles. Preferred Qualifications Certifications: Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), or Certified Kubernetes Security Specialist (CKS). Service Mesh: Practical experience implementing and managing service meshes for MTLS and advanced traffic shaping. Security: Experience with container vulnerability scanning, OPA Gatekeeper, or Kyverno for policy enforcement. Bachelors in Computer science or IT or any Engineering Company Benefits & Culture • Inclusive and diverse work environment • Opportunities for professional growth and development • Comprehensive health and wellness benefits

Job Description Job Description The Data Architect works in all data environments which includes data design, database architecture, metadata and repository creation. The Data Architect work assignments are varied and frequently require interpretation and Consultant determination of the appropriate courses of action.The Data Architect responsible for developing blueprints for all data repositories, evaluating hardware and software platforms, and integrating systems. Translates business needs into long-term data architecture solutions. Defines, designs and builds dimensional database schemas. Evaluates reusability of current data for separate analyses. Conducts data sheering to rid the system of old, unused or duplicate data. Reviews object and data models and the metadata repository to structure the data for better management and quicker access. Understands department, segment, and organizational strategy and operating objectives, including their linkages to related areas. Makes decisions regarding own work methods, occasionally in ambiguous situations, and requires minimal direction and receives guidance where needed. Follows established guidelines/procedures.Data Architecture & StrategyDefine and maintain enterprise data architecture standards, principles, and roadmaps.Design scalable data platforms supporting analytics, reporting, AI/ML, and operational workloads.Develop conceptual, logical, and physical data models for enterprise applications.Establish architecture patterns for data integration, master data management, and data quality.Cloud Data Platform LeadershipLead the design and implementation of cloud-based data platforms using technologies such as Snowflake, Prefect, Google Cloud Platform (Eligible to workP), Azure and DatabricksDefine best practices for data storage, processing, orchestration, and security.Guide migration of on-premises data assets to cloud environments.Data Engineering & IntegrationArchitect batch, real-time, and event-driven data pipelines.Design solutions for API integrations, ETL/ELT frameworks, and data virtualization.Ensure high-performance and scalable ingestion, transformation, and consumption of data.Governance & CompliancePartner with Data Governance teams to establish metadata management, lineage, stewardship, and data quality frameworks.

Job Description Job Description Introduction The role involves preparing the Strategic Process Inventory (SPI) data estate for use by the GenAI platform. The responsibilities include defining the data onboarding approach, identifying required source structures, designing performant access patterns, and ensuring metadata is complete, accurate, and usable by downstream semantic and AI context layers. Required Skills & Qualifications 8 years of experience in enterprise data architecture, database architecture, or data platform architecture. Strong experience with Oracle relational databases and enterprise data models. Experience designing performant data access patterns for analytics, reporting, or AI-enabled query systems. Experience with metadata onboarding, data catalogs, business glossaries, and semantic modeling. Advanced SQL, especially Oracle SQL. Strong understanding of PL/SQL concepts. Working knowledge of Python for metadata extraction, profiling, or automation is preferred. Familiarity with YAML / JSON metadata formats is useful. Prior work experience at client or in client's Industry. Applicants must be able to work directly for Artech on W2. Preferred Skills & Qualifications Experience with enterprise process management systems (POP, ARIS). Exposure to GenAI platforms and LLM-based enterprise solutions. Knowledge of regulatory and compliance-driven data environments. Experience with Airflow, dbt, Spark, or enterprise data pipeline tooling. Day-to-Day Responsibilities Identify and document the required SPI Oracle database schemas, tables, views, columns, keys, relationships, and constraints needed for GenAI. Define the onboarding scope for structured data, including source systems, subject areas, entities, and key data products. Extract, validate, and organize technical metadata from Oracle using tools such as Toad, SQL scripts, catalog exports, or database dictionary queries. Establish metadata standards for table descriptions, column definitions, data types, keys, data classifications, and business relevance. Work with business and data SMEs to validate whether the onboarded data accurately represents the enterprise process management business domain. Analyze SPI data structures to determine where direct source access may be inefficient for natural-language query workloads. Design optimized database views or materialized views to improve performance for GenAI query execution. Define aggregation, denormalization, join, and filtering strategies for commonly used SPI data access paths. Ensure materialized views preserve semantic correctness and do not introduce ambiguity into business reporting. Define refresh frequency, dependency management, and operational ownership for materialized views. Provide canonical source-to-target mapping between Oracle data structures and business concepts. Support the Knowledge / Data Engineer in mapping business terminology to physical Oracle tables and columns. Identify authoritative source fields for core SPI business terms, metrics, dimensions, and identifiers. Define reusable data access patterns that can be reflected in the semantic layer and AI context artifacts. Validate data quality, completeness, referential consistency, and metadata accuracy. Identify sensitive, restricted, or regulated data elements that require access controls or masking. Document known data limitations, latency, interpretation caveats, and usage constraints. Ensure data onboarding artifacts are versioned and traceable. For immediate consideration please click APPLY to begin the screening process with Alex.

Job Description Job Description Genesis10 is seeking a Data Architect for our client in the utilities industry. This long term contract position is located in Dallas, TX 77202. Hybrid schedule 2-3 days onsite. W2 Hourly Pay rate range: ( $85-120/hr Depending on experience ) Description: We are seeking a Data Architect to own the strategic design and governance of our enterprise data landscape, built on Oracle on-premise database platforms and modeled using Erwin. This role sits above individual project data models: you will define the enterprise-wide data architecture, standards, and target operating model that all data modelers, engineers, and DBAs build against, while personally handling the highest-complexity, highest-volume modeling and architecture decisions across the organization. You will bring proven experience architecting for large-scale data volumes (multi-GB to multi-TB), regulated environments, and the performance, scalability, and integrity demands that come with them. You will also be responsible for assisting in development and management of Data Governance and Master Data Management solutions. You must be comfortable presenting deep technical concepts to non-technical leadership i.e., have good technical and communication skills coupled with the ability to provide technical mentorship. Key Responsibilities Data Architecture & Data Strategy Define and own the enterprise data architecture strategy, including target-state data models, subject area models, and reference architectures across the Oracle on-premise estate. Establish enterprise-wide data modeling standards, naming conventions, and governance policies within Erwin, and ensure consistent adoption across data modeling and engineering teams. Own the enterprise Erwin model repository/mart: subject area organization, model versioning, complex merges, and cross-model consistency at scale. Partner with stakeholders (Application Teams, Enterprise Architecture, business unit leaders) to translate business strategy into a coherent, long-term data architecture roadmap. Evaluate and architect for scalability, performance, and maintainability of Oracle databases handling large data volumes (GB to multi-TB scale), including partitioning, indexing, and storage strategy at the architectural level. Assist in promoting the Data Architecture function to increase the adoption of Data Virtualization (Denodo) across the enterprise. Data Modeling & Design Oversight Design and review conceptual, logical, and physical data models for the most complex, cross-functional, and high-volume domains in the enterprise. Provide architectural review and approval of data models produced by senior/staff data modelers, ensuring alignment with enterprise standards, referential integrity, and downstream performance implications. Lead reverse-engineering and rationalization efforts for large, legacy Oracle schemas, consolidating and simplifying where architecturally sound. Guide both OLTP/3NF and dimensional (star/snowflake) modeling approaches, selecting the right pattern for transactional, operational, and analytical workloads. Governance, Performance & Risk Assist in enriching the enterprise data governance artifacts tied to the architecture: business glossary, data lineage, metadata repository, and data dictionary standards. Lead capacity planning and performance architecture for large Oracle databases anticipating growth in data volume and ensuring the model and physical design scale accordingly. Assess and mitigate architectural risk in schema changes at enterprise scale, including impact analysis across integrated systems. Ensure data architecture practices meet regulatory, security, and compliance requirements applicable to the industry. Establish policies, procedures and guidelines regarding all aspects of Data Governance Master Data Management Assist in establishment of policies, procedures and guidelines regarding all aspects of Master Data Management Ensure Architectural rules and design of the MDM process are documented and best practices are adhered to. Developing a strategic roadmap for MDM, and assisting in developing a roadmap and its implementation Leadership & Collaboration Mentor and provide technical direction to data modelers, ETL developers, and DBAs on modeling best practices, Erwin usage, and Oracle architecture patterns. Act as the primary architectural liaison between business stakeholders, application teams, DBAs, and infrastructure teams. Present architecture decisions, trade-offs, and roadmaps to senior leadership and non-technical stakeholders. Provide mentorship to Data Analysts to ensure data management and design best practices are adhered to. Collaborate with support teams to ensure consistent and proactive support methodologies are in place for all aspects of data movement and data transformation. Required Qualifications 10+ years of experience in data architecture, data modeling, or database engineering, including prior experience as a senior/lead data modeler, solution architect or data architect. Deep, hands-on expertise with Erwin Data Modeler at an enterprise scale (model mart, subject areas, complex compare/merge, versioning across large teams). Strong expertise in Oracle Database (on-premise), including advanced SQL/PL-SQL, schema design, partitioning, indexing strategy, and performance tuning at the architectural level. Demonstrated experience architecting and modeling for large data volumes (GB to multi-TB scale) with a track record of designs that scaled successfully in production. Strong command of data modeling theory (normalization/denormalization, cardinality, keys, referential integrity) and dimensional modeling (star/snowflake) for analytics. Experience defining enterprise data standards, governance frameworks, and metadata/lineage practices. Extensive working knowledge of all aspects of Data Movement and Processing, including Middleware, ETL, API, OLAP and best practices for data tracking Proven ability to operate at the intersection of technical architecture and executive stakeholder management i.e., translating business strategy into data architecture and communicating trade-offs to leadership. Strong written and verbal communication skills, with experience producing architecture documentation, ER diagrams, and data dictionaries for both technical and business audiences. Preferred Qualifications Experience in a regulated industry (utilities, financial services, insurance, healthcare) with associated data governance and compliance obligations. Experience leading or mentoring a team of data modelers/architects. Previous experience working with PostGres and MongoDB and big plus. Familiarity with complementary data modeling tools such as ER/Studio, Power Designer, Collibra, Alation Exposure to hybrid on-prem/cloud data strategies, even where the primary platform remains Oracle on-premise. Experience with Target Operating Model (TOM) design for data functions. Relevant certifications (OCI, DAMA, CDMP, etc.) is a plus. Experience with Hadoop/MongoDB is a plus Working experience with Denodo is a plus Team Culture: Our team is fast paced, fun, highly energetic, motivated and hardworking. We expect our candidates to be integrated into our results-driven and solution-oriented culture from the get-go. Our team attains high-quality results on challenging projects; the belief that outcomes are linked to one's effort rather than chance and the tendency to personally set challenging yet realistic goals. 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. 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 & 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 . click apply for full job details

Job Description Job Description Employment Type: Permanent/Direct Hire Compensation: $175k base/yr + Bonus & Benefits Location: 100% REMOTE We are seeking an experienced specialist to lead the configuration and implementation of Master Data Management (MDM) solutions using Informatica's IDMC MDM platform. This role involves configuring core MDM capabilities, such as data models, match and merge logic, survivorship rules, stewardship processes, workflows, hierarchy management, golden record creation, and data governance enablement. The ideal candidate will collaborate with business stakeholders, data governance teams, solution architects, integration teams, and data stewards to ensure high-quality master data across the enterprise. Requirements: Lead the configuration and implementation of Informatica IDMC MDM solutions for Customer, Product, and Supplier master domains. Configure and maintain MDM business entities, record models, relationships, hierarchies, and reference data structures. Design and configure match and merge rules, matching strategies, scoring models, thresholds, and survivorship logic. Manage golden record creation and maintenance processes. Define and implement data quality and standardization rules. Configure Data Governance and Stewardship capabilities, including user security, steward roles, and data issue management processes. Collaborate with stakeholders to define and implement data governance policies and data quality requirements. Support user acceptance testing, defect resolution, deployment activities, and production support. Work closely with integration and data engineering teams to ensure data onboarding and synchronization requirements are met. Develop and maintain configuration documentation, business rules, governance procedures, and operational runbooks. Preferred Qualifications: 7 years of MDM experience, including hands-on experience with Informatica MDM platforms. Extensive experience configuring MDM domains in IDMC. Strong experience with match and merge configuration, golden record management, and data stewardship processes. Deep understanding of master data management concepts and data quality practices. Strong SQL and data analysis skills. Demonstrated ability to leverage AI tools to enhance productivity and support data-informed task execution. Excellent stakeholder management and communication skills. Bachelor's degree in a related field. Open to travel (up to 25%, as needed). 26-01179

Job Description Job Description Test Lead Location: Indianapolis, IN Work Mode: Onsite Experience Required: 8-10 years Minimum Experience: 6+ years in Software Testing / QA Lead Experience: 2+ years in a Lead or Senior QA role Primary Skill: Automation Testing Business Vertical: CL-LSHC Child: IS-LSHC-3.2 Parent: IS-LSHC-3-Life Sciences NA-Parent Requisition ID: Role Summary Define and drive the testing strategy for one or more product teams. Lead and mentor a team of QA/Test Engineers. Own the overall quality of software releases . Partner with: Product teams Development teams Operations Business analysts DevOps teams Ensure software: Meets requirements Is delivered on schedule Is reliable in production Meets defined quality standards Combine hands-on technical expertise with: People leadership Strategic planning Quality management Test Strategy & Planning Define: Test strategy Test plans Test estimates Testing schedules Testing scope Entry and exit criteria Testing deliverables Establish quality metrics aligned with project goals and release schedules. Assess testing risks and prioritize efforts across: Functional testing Regression testing Integration testing System testing Performance testing Security testing User Acceptance Testing (UAT) Estimate testing effort. Contribute to: Sprint planning Release planning Quality planning Identify risks early and develop appropriate mitigation strategies. Team Leadership Lead, mentor, and coach QA/Test Engineers. Assign work and manage team workload. Coordinate daily activities across onsite and offshore testing teams . Monitor team progress and remove delivery impediments. Conduct performance reviews. Support career development. Participate in hiring activities. Mentor team members and promote best practices. Foster a culture of: Quality ownership Accountability Continuous improvement Quality-first delivery Test Execution & Automation Oversee design and execution of manual and automated test cases . Lead: Functional testing Integration testing System testing Regression testing UAT Release validation Drive the test automation strategy . Evaluate and select automation frameworks. Integrate automated testing into CI/CD pipelines . Review test coverage. Identify automation opportunities. Improve: Regression coverage Test execution efficiency Test suite reliability Quality controls Continuously improve the testing process and automation framework. Test Documentation & Quality Management Review: Test scenarios Test cases Test data Requirements traceability Execution evidence Defect documentation Ensure testing documentation is complete and accurate. Maintain requirements traceability throughout the testing lifecycle. Ensure testing deliverables meet quality standards. Defect Management Manage the complete defect lifecycle . Facilitate defect triage meetings. Prioritize critical defects. Drive root-cause analysis discussions. Track defect resolution and ensure timely closure. Communicate critical defects, risks, and blockers to stakeholders. Support production incident analysis and defect prevention. Collaboration & Stakeholder Management Work closely with: Product Owners Developers DevOps Business Analysts Infrastructure Teams Data Teams Security Teams Release Management Business Users Client Stakeholders Clarify requirements and acceptance criteria. Assess requirements for testability. Identify quality and delivery risks early. Communicate: Testing status Risks Issues Blockers Release readiness Coordinate with vendors and offshore teams where applicable. Provide accurate status updates to project managers and senior leadership. Reporting & Metrics Publish accurate: Test status dashboards Quality metrics Risk logs Issue logs Release readiness recommendations Track quality and testing KPIs. Drive improvements in: Escaped defects Production incidents Automation coverage Regression cycle time Release quality Compliance & Production Support Ensure adherence to: Client processes Quality standards Documentation requirements Audit controls Regulatory requirements Compliance expectations Support: Production deployments Post-release validation Production incident analysis Continuous improvement initiatives Required Qualifications Bachelor's degree in: Computer Science Engineering Information Systems Related field Equivalent professional experience may be considered. 6+ years of Software Testing / QA experience. 2+ years in a Test Lead or Senior QA role. Strong knowledge of: SDLC STLC Agile Scrum methodologies Experience with test management and defect tracking tools such as: Jira Strong written and verbal communication skills. Ability to influence technical and business stakeholders. Preferred Qualifications ISTQB Advanced Level - Test Manager certification or equivalent. Experience testing cloud-based applications , including: AWS Azure GCP Experience testing microservices architectures . Experience with test automation and CI/CD integration. Key Competencies Leadership and mentoring Test strategy and planning Automation testing Analytical thinking Risk-based testing Attention to detail Quality mindset Organization and prioritization Problem-solving Adaptability Stakeholder management Communication Team collaboration Defect management Continuous improvement Success Measures Reduction in escaped defects . Reduction in production incidents . Increased automation coverage. Faster regression testing cycles. On-time, high-quality software releases. Improved test efficiency and reliability. Strong team engagement. Team member growth and retention. Key Technologies / Keywords Test Lead QA Lead Software Testing Quality Assurance Automation Testing Test Automation Manual Testing Functional Testing Integration Testing System Testing Regression Testing UAT Release Validation Test Strategy Test Planning Defect Management Jira SDLC STLC Agile Scrum CI/CD Microservices AWS Azure GCP ISTQB Risk-Based Testing Test Metrics Quality Metrics