Data Migration Engineer

NTT DATA North America is a global business and technology services company focused on consulting, data and artificial intelligence, applications, infrastructure, and connectivity. The Senior Data Migration Engineer will design and implement Python-based extraction and loading pipelines, dbt transformations, and Airflow orchestration to migrate enterprise-scale workflows from Informatica PowerCenter to a modern data stack.

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
• Experience with SQLAlchemy, cx_Oracle, or pyodbc for Python-based database connectivity
• Experience mentoring junior and mid-level engineers in offshore delivery models