Data Migration Engineer

Required Skills & Experience

• 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

• 3+ 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

Nice to Have Skills & Experience

• Experience with SQLAlchemy, cx_Oracle, or pyodbc for Python-based database connectivity

• Experience mentoring junior and mid-level engineers in offshore delivery models

Job Description

Role Overview

o The Senior Data Migration Engineer serves as a hands-on technical contributor and delivery anchor, responsible for 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.

o This role requires deep expertise in converting complex Informatica workflows into Python, dbt, and Airflow, and the ability to deliver production-quality, functionally equivalent output at enterprise scale.

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.