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Popular data engineer role, mid-level experience, metro location, and visible employer increase candidate competition.
Role requires specific Databricks/Azure experience so skills are transferable but moderately tied to platform expertise.
Explicit 3+ years plus mandatory Databricks, PySpark, Azure and CI/CD requirements create strict shortlisting filters.
Design, build, test, and maintain scalable ELT data pipelines using Databricks (Unity Catalog, Delta Live Tables, Databricks Asset Bundles), PySpark, and SQL.
Develop silver/gold layer data models within medallion architecture to support enterprise reporting and Power BI.
Implement platform governance, CI/CD practices (GitHub Actions), automate workflows, and maintain pipeline documentation while collaborating on technical scoping with the Head of Data & Analytics.
3+ years experience designing and building scalable distributed data pipelines and dimensional data models.
3+ years experience in Python and SQL, with mandatory experience in Databricks platform and PySpark (Unity Catalog, DABs, DLT).
Experience with Azure data services including ADLS Gen2, Azure Key Vault, and Azure SQL.
Work Experience Required: At least 3 years related to data engineering; Notice Period: Not explicitly mentioned in the JD.
Proven expertise operating within Azure cloud environments using Databricks and implementing medallion architecture for data modeling and transformation.
Experience driving automation and DevOps best practices with CI/CD pipelines for data solution deployment.
Ability to contribute technically during scoping and integrate API-based data solutions, showing ownership of end-to-end scalable data pipeline delivery.