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Specialized Databricks/Azure stack and US work-authorization reduce applicants despite mid-level data role and remote visibility.
Core Databricks, Azure, and PySpark skills are transferable, though insurance preference increases domain specificity moderately.
Explicit 5–7+ years and mandatory Databricks/Azure/Unity Catalog skills create strict technical shortlisting filters.
Build, integrate, and operationalize enterprise data architecture on Databricks and Azure platform.
Design, develop, and maintain scalable data pipelines, transformation logic, and analytics-ready datasets using PySpark, SQL, Azure Databricks, and Azure Data Factory.
Implement and enforce data governance, security policies; monitor, tune, and optimize data platform performance and CI/CD pipelines with Azure DevOps.
5–7+ years of Data Engineering experience including production-grade pipeline development.
Hands-on experience with Azure Databricks, Azure Data Factory, Delta Lake, Unity Catalog, PySpark, and SQL.
Bachelor's degree in CS, Engineering, Data Science or equivalent practical experience (desired).
Must be legally authorized to work in the United States; position is fully remote within US with possible periodic in-person meetings.
Experienced with end-to-end data platform ownership including data quality, validation, security, and CI/CD process.
Capable of collaborating cross-functionally between technical and non-technical stakeholders in an agile delivery environment.
Exposure to insurance domain data and familiarity with business intelligence tools (Power BI) or AI/automation in data workflows is a plus.