Senior DataStage Developer

Senior DataStage Developer

Objective
Drive the end-to-end rationalization, reverse-engineering, and automated validation of legacy DataStage environments migrating to modern Databricks architectures. This role is critical to eliminating legacy code redundancies, mapping complex data lineage, and implementing automated testing frameworks to guarantee zero data loss and business disruption during system cutovers.

Key Responsibilities

• Legacy Rationalization: Analyze DataStage .dsx/.isx exports and metadata to map end-to-end data lineage.
• Code Elimination: Identify and isolate "dead jobs", redundant code, and duplicate logic to streamline migration waves.
• Technical Translation: Provide functional logic explanations of complex parallel/server jobs to the PySpark development team.
• Test Automation: Deploy automated test frameworks to execute large-scale data reconciliation between DataStage and Databricks.
• Data Validation: Build automated scripts to validate data schemas, row counts, and complex transformations across dual-run environments.
• Regression Testing: Execute regression testing on newly refactored PySpark code against historical legacy data.
• Migration Sign-off: Document validation execution KPIs and formally sign off on data accuracy before live migration cutovers.

Technical Skills & Competencies

• Legacy ETL: IBM InfoSphere DataStage (Parallel/Server jobs, Sequences) and operational metadata analysis.
• Data Quality & Testing: Automated ETL Testing tools, PyTest, and Great Expectations.
• Languages & Querying: Advanced SQL, Python, and XML/JSON parsing.
• Target Platforms: Familiarity with Databricks, PySpark, and modern cloud data warehouses.