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Mid-level generic Data Engineer title but niche Microsoft Fabric requirement reduces applicant density.
Core data engineering skills are transferable, but Microsoft Fabric specialization and insurance-data preference increase specificity.
Mandatory 5+ years plus specialized Microsoft Fabric, Azure, PySpark, Purview, and CI/CD requirements enforce strict filtering.
Develop and maintain multi-layer Microsoft Fabric / OneLake Lakehouse solutions (Bronze, Silver, Gold) including ingestion, transformation, and curated datasets.
Build scalable, reusable data ingestion pipelines and CDC frameworks from diverse sources and implement data quality, validation, tracking, and error-handling frameworks.
Collaborate with architects and business teams to troubleshoot production issues, optimize Spark/PySpark, Python, SQL workloads, and support Power BI semantic models and Direct Lake consumption.
5+ years of Data Engineering experience with hands-on Azure / Microsoft Fabric expertise.
Strong proficiency in Microsoft Fabric Lakehouse, OneLake, Data Pipelines, Notebooks; Spark/PySpark, Python, SQL, and Delta Lake.
Experience with ETL/ELT, CDC, Medallion Architecture, data quality and validation frameworks.
Experience with Microsoft Purview, Azure DevOps, Git, CI/CD; Commercial insurance or brokerage data experience preferred but not mandatory.
Experienced in designing and operationalizing end-to-end lakehouse architectures using Microsoft Fabric spanning ingestion to curation.
Proficient in building robust, operational data quality and governance frameworks in regulated data environments.
Able to partner effectively with cross-functional technical and business stakeholders for scalable data platform delivery.