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Key Responsibilities

• Assess complex Informatica workflows, including sessions, mappings and parameterizations, and translate them into equivalent Python EL scripts and dbt transformation models.
• Develop and maintain Python EL pipelines that load high-volume data, including billion-row tables, into the target warehouse using SQLAlchemy, cx_Oracle, pyodbc, and bulk export tools such as Oracle Data Pump and SQL Server BCP.
• Design and develop dbt transformation models based on Informatica mapping logic, applying dbt best practices such as model layering, macros, incremental strategies and snapshot patterns.
• Develop dbt-native tests and custom Python unit tests to validate transformation correctness and data quality.
• Develop Airflow DAGs that orchestrate Python EL and dbt scripts end-to-end, producing output functionally equivalent to the source Informatica workflows.
• Contribute to the GitLab CI/CD pipeline for dbt and Airflow code, including lint gates, automated testing and deployment to shared NAS.
• Perform peer code reviews and give constructive technical feedback to fellow engineers.
• Troubleshoot performance issues and data discrepancies during SIT and UAT, including row-count reconciliation between source Oracle/SQL Server systems and the target warehouse.
• Contribute to technical documentation, runbooks and handover materials.