Data Platform Engineer (102-08SENG-01)

This role converts a large Azure Data Factory estate into Databricks workflows on AWS. The scope for year one: 2,094 ADF pipelines to migrate — built as reusable templates rather than one-by-one — 9,859 pipeline activities to translate (some map directly, others need rewriting as Lambda or Step Functions), 471 Spark dataflows to move onto Databricks on AWS, and 4 Databricks workspaces (Dev, QA, Pre-prod, Prod) to rehost, including notebook paths and Unity Catalog rewiring. This is a regulated environment, so reconciling migrated data against source systems is part of the definition of done, not an afterthought.

• Convert Azure Data Factory pipelines into Databricks workflows on AWS, building reusable templates rather than migrating one at a time.
• Rehost Databricks workspaces onto AWS and migrate ADLS Gen2 storage to S3.
• Rewrite ADF Web Activities as Lambda functions or Step Functions tasks, and replace ADF-specific scaling with native Databricks mechanisms.
• Build and tune PySpark transformations for production data volumes.
• Replace Azure Synapse Serverless with Databricks SQL Warehouse.
• Reconcile migrated data against source systems as part of the definition of done.

• Production experience with Databricks: workspaces, jobs and workflows. The central skill for this role.
• Strong Spark and PySpark experience for real data volumes, including tuning.
• Production-grade Python.
• Experience building or migrating Azure Data Factory pipeli