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Generalist mid-level Data Engineer in metro at a well-known agency increases competition.
Databricks, PySpark and Azure data engineering skills are broadly transferable across industries.
Mandatory 3+ years plus Databricks, PySpark and Azure experience enforces strict shortlisting.
Design, develop, test, and maintain scalable data pipelines using Databricks (Unity Catalog, DABs, DLT), PySpark, and SQL for AUNZ region.
Manage data workflows and data models in a medallion architecture to support enterprise-scale transformation and Power BI reporting.
Implement secure platform governance, CI/CD with GitHub Actions, execute data migrations, and maintain clear documentation of data engineering components.
3+ years of experience designing and building scalable distributed data pipelines and dimensional data models.
3+ years of experience in Python and SQL programming.
Experience required in Databricks platform (including Unity Catalog, DABs, DLT) and Azure data services (ADLS Gen2, Azure Key Vault, Azure SQL).
Understanding of CI/CD and Agile development practices including unit and integration testing.
Experienced in implementing data solutions on Azure Databricks with focus on automation and architectural best practices.
Capable of technical scoping and delivering solutions closely aligned with business requirements and collaborating with senior analytics leadership.
Familiar with secure platform governance, data lineage, and DevOps deployment workflows within an enterprise environment.