Lead the migration of legacy IBM DataStage ETL workloads to modern Databricks/Spark on AWS, designing scalable cloud data pipelines with PySpark, Python, and SQL. Focus on data validation, CI/CD automation, and seamless production cutover while decommissioning outdated systems. Requires deep expertise in ETL modernization, Delta Lake, and AWS data services.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
ETL Modernization Developer
Location: Remote
Duration: 12 Months Contract
Payrate on: W2 (No C2C)
Work Authorization: GC / USC Only
Job Summary
Seeking an experienced ETL Modernization Developer to migrate and modernize legacy IBM DataStage workloads to Databricks/Spark on AWS. The ideal candidate should have strong hands-on experience in ETL modernization, PySpark/Python, SQL, AWS data services, Delta Lake, and CI/CD.
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Must-Have Skills
- IBM DataStage – strong hands-on development
- ETL/ELT Migration & Modernization – legacy-to-cloud migration
- Databricks + Apache Spark on AWS
- PySpark, Python, SQL & Shell scripting
- Delta Lake, Unity Catalog & Photon
- AWS Glue, Lambda & Redshift
- CI/CD + Automated ETL Testing
- PyTest + XML/JSON parsing
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Key Responsibilities
- Assess and migrate legacy DataStage ETL/ELT jobs to Databricks/Spark.
- Build scalable cloud data pipelines using PySpark/Python/SQL.
- Perform data validation, parity checks, UAT, regression and performance testing.
- Implement CI/CD and automated ETL testing.
- Support production cutover, deployment, stabilization and hypercare.
- Decommission legacy DataStage processes after successful migration.
- Prepare technical documentation and conduct knowledge transfer.
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