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Mid-level, metro Data Engineer role with common skillset and broad requirements increases candidate competition.
Medium—data engineering skills transfer broadly, but Microsoft Fabric and insurance preference add bias.
High due to explicit 5+ years and mandatory Microsoft Fabric, Spark/PySpark, and Azure skills.
Own end-to-end design, development, and maintenance of Microsoft Fabric/OneLake Lakehouse solutions across Bronze, Silver, and Gold data layers.
Build and optimize scalable data pipelines using Spark/PySpark, Python, SQL, and Fabric Data Pipelines, including reusable ingestion and CDC frameworks from diverse sources.
Implement data quality, validation, reconciliation, monitoring, and governance controls, ensuring secure, high-quality datasets for business intelligence and analytics consumption.
Minimum 5 years of Data Engineering experience with hands-on Azure / Microsoft Fabric expertise.
Proficiency in Spark/PySpark, Python, SQL, Delta Lake, and experience with ETL/ELT processes, CDC, and Medallion Architecture.
Strong experience building Microsoft Fabric Lakehouse, OneLake, data pipelines, notebooks, and knowledge of data governance tools like Microsoft Purview.
Work Experience Required: Minimum 5+ years data engineering; Commercial insurance or brokerage domain experience preferred but not mandatory.
Experienced in building layered data architectures (Bronze/Silver/Gold) and operationalizing robust data quality and exception-handling frameworks.
Skilled in collaboration with architects, BI teams, and stakeholders to deliver scalable data solutions in Azure/Microsoft Fabric environments.
Familiar with deployment and source control technologies like Azure DevOps, Git, CI/CD pipelines, supporting enterprise-grade data platform operations.