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.

📌 Data Migration Engineer (Fall 2026) (India)
🏢 NTT Data
📍 India