Join NTT DATA as a Data Migration Engineer and drive a large-scale migration from Informatica PowerCenter to a modern data stack. This role offers an exciting opportunity to work with cutting-edge technologies and contribute to innovative projects.

As a key technical contributor, you will design and implement robust data pipelines using Python, dbt, and Airflow. Your expertise will be crucial in converting complex legacy workflows into efficient, scalable solutions for enterprise environments.

We are seeking individuals passionate about innovation and growth within an inclusive and forward-thinking organization. Become part of a team that is shaping the future of digital infrastructure and AI.

Translate intricate Informatica PowerCenter workflows, including sessions, mappings, and parameterizations, into equivalent Python EL scripts and dbt transformation models.

Develop and maintain Python EL pipelines for high-volume data ingestion, leveraging tools like SQLAlchemy, cx_Oracle, and pyodbc, along with bulk export utilities such as Oracle Data Pump and SQL Server BCP.

Design and construct dbt transformation models adhering to Informatica mapping logic, implementing dbt best practices like model layering, macros, incremental strategies, and snapshot patterns.

Create dbt-native tests and custom Python unit tests to ensure transformation accuracy and data quality.

Orchestrate Python EL and dbt scripts end-to-end using Airflow DAGs, ensuring functional equivalence with source Informatica workflows.

Contribute to GitLab CI/CD pipelines for dbt and Airflow code, incorporating lint gates, automated testing, and deployment to shared NAS.

Conduct peer code reviews, offering valuable technical feedback to engineering colleagues.

Diagnose and resolve performance bottlenecks and data discrepancies during SIT and UAT, including row-count reconciliation between source systems and the target warehouse.

Author comprehensive technical documentation, runbooks, and handover materials.

A minimum of 5 years of hands-on experience with Informatica PowerCenter, covering mappings, sessions, workflows, and parameterization is essential.

Demonstrate at least 3 years of practical experience with dbt Core, including proficiency in model layering, macros, testing, and incremental materializations.

Possess significant experience with Airflow, including DAG authoring, managing task dependencies, and integration with scheduling tools.

Require a strong foundation of 5+ years in Python, with proven production experience in parallel and batch data processing techniques.

Exhibit 5+ years of SQL expertise, capable of handling complex joins, window functions, and aggregations on extensive datasets.

Experience with Oracle Data Pump (expdp/impdp) or SQL Server BCP / BULK INSERT for efficient high-volume data movement is necessary.

Preferred qualifications include familiarity with SQLAlchemy, cx_Oracle, or pyodbc for Python database connectivity and experience mentoring junior engineers in offshore delivery models.