Data Engineer

Sr. Data Engineer (x2 Roles)

Remote

Contract

These two roles sit at the core of Companies data lake modernization initiative. We are building a medallion architecture (Bronze / Silver / Gold / Feature Store) on Microsoft Fabric and OneLake that will power our Paragon AI identification engine. Sr. Data Engineers will design and build the ingestion, transformation, and enrichment pipelines that turn raw health plan, legal, and P&C claims data into structured intelligence signals — all while maintaining strict HIPAA compliance and honoring data contractual constraints across our 119 client contracts.

Key Responsibilities:

• Design and build data ingestion pipelines from multiple sources including health plan claims, P&C clearinghouse data, and Bloomberg Law legal filings into the Bronze layer of the medallion architecture
• Develop Silver layer transformation logic: normalization, deduplication, entity matching (member identity resolution across sources), and schema enforcement
• Build Gold layer aggregations and enriched datasets that feed Paragon scoring models and Power BI reporting
• Maintain Feature Store pipelines that produce ML-ready feature sets for Data Science team consumption
• Enforce Verisk data contractual constraints — Verisk-sourced data must remain stateless and cannot be persisted in the Fabric lake or used for model training
• Support multi-tenant data isolation requirements across 119 client contracts; implement appropriate partitioning and access control patterns
• Collaborate with the ML Engineering team to deliver features that support model retraining and scoring pipelines
• Build and maintain data quality validation scripts (Python) and monitoring on pipeline health
• Document lineage, transformations, and data contracts within Confluence

Requirements:

• 5+ years of data engineering experience, preferably on Azure or Microsoft Fabric
• Strong Python and SQL skills; experience with medallion/lakehouse architecture patterns
• Experience with Microsoft Fabric, OneLake, Azure Data Factory, or equivalent orchestration tools
• Familiarity with healthcare data formats (claims, eligibility, EDI 837/835) is a strong plus
• Understanding of data governance in multi-tenant or regulated environments
• Strong async communication skills for collaboration with U.S.-based Data Science and Engineering leads