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Popular mid-level Data Engineer title with generalist appeal and common experience band, moderate competition.
Specialized Databricks governance reduces transferability, but core data engineering skills remain moderately transferable.
Mandatory Databricks, Delta Lake, Unity Catalog, advanced SQL and Python increase screening strictness.
Design, develop, and maintain production-grade data pipelines using Databricks and Delta Lake with a focus on REST API data integration.
Implement and optimize data models, SQL queries, and data quality frameworks to ensure scalable, reliable, and governed data solutions.
Manage Databricks Unity Catalog for data governance and oversee production operations including monitoring, troubleshooting, and CI/CD deployment of data pipelines.
Hands-on experience as a Data Engineer with strong expertise in Databricks, Delta Lake, Databricks SQL, Databricks Workflows, Unity Catalog, advanced SQL, and Python.
Proven ability to develop enterprise-grade data pipelines involving REST API integrations and dimensional data modelling.
Experience implementing data quality frameworks and managing production data engineering operations.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with enterprise data pipeline development and production operations in a governed Databricks environment emphasizing data governance and security.
Comfortable with complex data orchestration, incremental API ingestion, and data quality automation in scalable data architectures.
Familiar with Azure data ecosystem, Medallion Architecture, Delta Live Tables, and cloud-based CI/CD practices for data engineering deployments.