Contract AI Data Engineer

Team: Information Technology

Location: Chicago, IL

Commitment: Contract

Workplace Type: hybrid

Responsibilities

Own the data platform

• Own Bronze / Silver / Gold pipelines in Microsoft Fabric and OneLake
• Model governed semantic layers; serve Power BI via Direct Lake
• Ingest business-unit data into Fabric & Azure SQL with quality and lineage controls
• Enforce data governance, security, and PII handling aligned to Entra ID
• Expose curated datasets to AI agents through approved MCP servers only
• Use Claude Code to build pipelines against JSSI standards; review and validate all AI-generated code before it ships
• Orchestrate, monitor, and optimize pipelines for reliability, performance, and Fabric capacity (CU) cost
• Manage Git-based version control and Fabric deployment pipelines across dev / test / prod

Support reporting and ad-hoc requests

• Handle ad-hoc requests (report enhancements and fixes, and dataset enhancements and fixes) across Microsoft Fabric and Power BI
• Build and maintain paginated (operational) reports
• Write, debug, and tune SQL for reporting, data investigation, and fixes
• Use Claude Code to investigate and diagnose platform, data-quality, and reporting issues, tracing root cause across pipelines, lake house tables, and semantic models before drafting a validated fix
• Support and optimize Power BI semantic models and DAX for downstream consumers

Requirements

Required

Hands-on experience building and maintaining data pipelines in Microsoft Fabric, including Lakehouse architecture and OneLake

Proficiency with Bronze / Silver / Gold medallion architecture and semantic layer modeling

Experience with Azure SQL, ADLS Gen2, and data ingestion across multiple source systems

Understanding of data governance, security, and PII handling practices, including Entra ID alignment

Experience exposing data products via APIs or MCP-style interfaces for downstream AI or analytics consumption

Active use of AI coding tools (such as Claude Code) as part of your development workflow — not aspirational, but current practice

Strongly preferred

Experience building data infrastructure specifically to support AI agents, ML models, or agentic pipelines

Familiarity with Power BI and Direct Lake connectivity

Experience working within engineering standards, documentation-first workflows, and structured code review practices

Exposure to MCP (Model Context Protocol) servers or similar AI data access patterns

Not required

People management experience — this is an individual contributor role

Aviation or MRO domain knowledge — curiosity and the ability to learn the business context matters more than knowing it on day one

WHO THRIVES IN THIS ROLE

This role is a great fit for someone who takes genuine ownership of data infrastructure — not just someone who builds pipelines when tickets arrive, but someone who thinks about the platform as a product with real consumers. You are already using AI tools to write and ship code faster. You care about data quality as a first principle, not a nice-to-have. And you want to be part of building something that directly enables the AI-first future of a company, not supporting a legacy stack.