Data Engineer, Microsoft Fabric and AI Director

GS1 Global Office seeks a senior, hands-on Data Engineer Director (individual contributor) to design, build, and support secure, scalable enterprise data and analytics solutions. The role focuses on Microsoft Fabric, Azure data services, and Power BI, with responsibility for AI-enabled data pipelines that connect approved enterprise data to large language model platforms such as Claude AI.

In this onsite role in Ewing, NJ, you will deliver production data engineering and analytics capabilities that span lakehouse and warehouse architectures, enterprise semantic models, and operational reporting. You will also develop retrieval-augmented generation (RAG) pipelines, including data preparation, chunking, embeddings, indexing, and retrieval workflows that enable accurate and traceable AI-enabled search and analytics. The position includes technical leadership on data architecture, engineering standards, and responsible AI implementation.

• Design, develop, and maintain scalable data pipelines using Microsoft Fabric and Azure data services
  .
• Build and support Lakehouse
  , Data Warehouse
  , and semantic model solutions using appropriate architecture and reusable design patterns.
• Develop reliable data integration processes using Microsoft Fabric Data Pipelines
  , Azure Data Factory
  , APIs
  , and other approved integration methods.
• Support migration and modernization initiatives involving Microsoft Fabric and Azure analytics services.
• Optimize performance, scalability, maintainability, and cost efficiency for data processing.
• Contribute to enterprise data architecture decisions, including evolution of shared data models and analytics standards.
• Design and build RAG pipelines to securely connect approved enterprise data to Claude AI and other approved large language model platforms.
• Develop data preparation and retrieval components for AI-enabled search and analytics, including chunking
  , embedding
  , indexing
  , and retrieval
  .
• Support responsible adoption of approved enterprise AI and development tools, including Claude AI and Claude Code
  , with secure data-handling and access patterns.
• Evaluate and prototype AI-enabled analytics use cases with senior leaders and technical stakeholders, focusing on business value, architecture, risk, and guardrails.
• Monitor and improve AI pipeline reliability, quality, performance, and cost in alignment with GS1 governance standards.
• Maintain documentation, traceability, and human oversight for AI-enabled solutions.
• Develop and maintain Power BI dashboards, reports, datasets, and semantic models for actionable insights.
• Support operational reporting, data-quality reporting, and prioritized ad hoc analytics requests.
• Define acceptance criteria with business stakeholders and translate requirements into sustainable reporting solutions.
• Promote consistent definitions, measures, and reporting practices across the organization.
• Implement data validation, observability, monitoring, and quality controls across pipelines and analytics solutions.
• Support metadata management, data lineage, documentation, retention, and governance requirements.
• Design solutions according to GS1 information security, data privacy, access-control, and responsible AI requirements, including role-based access controls
  , data classification
  , and auditability.
• Identify and elevate data-quality, security, privacy, model-risk, and governance concerns.
• Develop automated testing and validation for data pipelines, semantic models, reports, and AI-enabled solutions.
• Use Git
  , source control,
  CI/CD
  , and environment management to support deployment across development, test, and production.
• Monitor critical solutions, resolve production incidents, and troubleshoot pipeline failures, refresh errors, reporting issues, RAG pipeline errors, and performance bottlenecks.
• Conduct root-cause analysis and implement preventative improvements.
• Maintain technical documentation, operational runbooks, and recovery procedures, contributing to release validation and business-continuity activities.
• Provide technical leadership on data architecture, solution design, engineering standards, and responsible AI implementation.
• Review code and solution designs, share knowledge, and coach team members in data engineering and analytics practices.
• Partner with Product Owners, Data Engineers, QA, Software Engineering, and business stakeholders across a globally distributed organization.
• Communicate technical options, dependencies, risks, and costs to technical and…