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The role involves migrating complex Informatica workflows to Python EL scripts and dbt transformation models. You will also be responsible for orchestrating these pipelines using Airflow and ensuring data quality through rigorous testing and peer reviews.
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 to land 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, incorporating dbt best practices including model layering, macros, incremental strategies, and snapshot patterns.
• Develop dbt-native tests as well as custom Python unit tests to validate transformation correctness and data quality.
• Develop Airflow DAGs to orchestrate Python EL and dbt scripts end-to-end, producing output that is functionally equivalent to the source Informatica workflows.
• Contribute to GitLab CI/CD pipeline for dbt and Airflow code, including lint gates, automated testing, and deployment to shared NAS.
• Perform peer code reviews and provide 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.
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