Data Bricks Lead Engineer
Role details
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Tech stack
Job description
We are seeking a DatabricksEngineer to build of a new Databricks solution that ingests source files and constructs a semantic/serving layer that powers a Power BI dashboard. A semantic layer already exists; the new solution must conform to the same structure so that a replicated Power BI solution works seamlessly against it with no rework to reports, measures, or relationships. The engineer owns the Databricks data and semantic layer and partners with a dedicated Power BI developer/team, who own the dashboard build, to deliver the end solution., * Lead the design and delivery of file-ingestion pipelines in Azure Databricks (batch and/or streaming) that land and process incoming files into Delta Lake using a Medallion architecture (Bronze ? Silver ? Gold).
- Design the Gold/serving layer to replicate the existing semantic model exactly - matching table names, grain, column names, data types, keys, and relationships so the existing Power BI dataset can be repointed without redesign.
- Expose the model through Databricks SQL endpoints (Direct Query) so the Power BI developer can connect and validate the dashboard with no redesign.
- Collaborate with the Power BI developer/team as the data-side owner - align on the semantic contract (star schema, measures, RLS expectations), support their dashboard build, and resolve any data or model issues to land the end deliverable.
- Document the semantic mapping and work with the Power BI team to reconcile the replicated dashboard's output against the existing solution to prove parity.
Requirements
- AWS Databricks, Delta Lake, Medallion architecture, Unity Catalog
- Python and strong SQL
- Databricks SQL endpoints and a working understanding of Power BI semantic modeling (star schema, DAX, incremental refresh, RLS) sufficient to define and hand off the semantic contract
- Databricks Certified Data Engineer (Professional preferred)
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