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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 One Lake 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, One Lake, 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
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