Jobs → Data & Analytics → Data Migration Engineer

Data Migration Engineer

Mayee SamarthapuRemoteSENIORPosted 3d ago
PythondbtAirflowInformatica PowerCenterSQLAlchemycx_OraclepyodbcOracle Data PumpSQL Server BCP
About the Role We are looking for a Data Migration Engineer to join our team. This role focuses on designing and implementing Python-based extract/load pipelines, dbt-based transformations, and Airflow-based orchestration for a large-scale migration from Informatica PowerCenter to a modern data stack. 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. Requirements • 5+ years of Informatica PowerCenter experience - mappings, sessions, workflows, and parameterization • 3+ years of hands-on dbt Core experience - model layering, macros, tests, incremental materializations • Any number of years of Airflow experience - DAG authoring, task dependencies, and incorporation with scheduling tool • 5+ years of Python experience, including production use of parallelism and batch data processing • 5+ years of SQL experience - complex joins, window functions, aggregations across large datasets • Experience with Oracle Data Pump (expdp/impdp) or SQL Server BCP / BULK INSERT for high-volume data movement

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