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Medium: metro location but senior level and niche Microsoft Fabric skills moderate applicant density.
Medium: core data engineering skills transfer, but Microsoft Fabric specialization and insurance preference increase domain specificity.
High: explicit 8+ years and mandatory Microsoft Fabric/Azure, Spark, Purview, Power BI and domain experience.
Own the development and maintenance of Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers following Medallion Architecture.
Build and optimize scalable data ingestion and transformation pipelines using Spark/PySpark, Python, SQL, Fabric Data Pipelines, Synapse Pipelines, and Notebooks.
Implement data quality, validation, audit logging, schema validation, monitoring, and operational controls while supporting Power BI semantic models and ensuring compliance with data governance and security standards.
8+ years of data engineering experience with hands-on experience in Azure and Microsoft Fabric.
Proficiency in Spark/PySpark, Python, SQL, Delta Lake, and strong experience with Microsoft Fabric Lakehouse, OneLake, Data Pipelines, and Notebooks.
Bachelor's degree (B.Tech or equivalent) in Computer Science, Engineering, IT, or related fields.
Experience with ETL/ELT, CDC frameworks, Medallion Architecture, data quality frameworks, and knowledge of Power BI semantic models and Direct Lake.
Experienced in building scalable, layered lakehouse data architectures using Microsoft Fabric and Medallion Architecture.
Skilled in developing resilient data pipelines with strong operational maturity including error handling, schema drift detection, and monitoring.
Able to collaborate effectively with architects, BI teams, and stakeholders to deliver robust data solutions, preferably with familiarity in commercial insurance or brokerage data.