Data Migration Engineer

NTT DATA BUSINESS SOLUTIONS; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

NTT DATA BUSINESS SOLUTIONS in Bangalore, Karnataka, India seeks a Senior Data Migration Engineer to design and implement Python EL pipelines, dbt transformations, and Airflow orchestration for large-scale migrations from Informatica PowerCenter to a modern data stack.

The role requires deep expertise in converting Informatica workflows into Python, dbt, and Airflow, delivering production-quality outputs at enterprise scale, and contributing to CI/CD pipelines for dbt and Airflow deployments.

Qualifications

• 5+ years of Informatica PowerCenter experience including mappings, sessions and parameterization.
• 3+ years of hands-on dbt Core experience with models, macros and tests.
• 5+ years of Python experience including parallelism and batch data processing.
• 5+ years of SQL experience covering complex joins and window functions.
• Experience with Oracle Data Pump (expdp/impdp) or SQL Server BCP for high-volume moves.

Responsibilities

• Assess Informatica workflows and translate into Python EL scripts and dbt models.
• Develop and maintain Python EL pipelines to land high-volume data into the target warehouse.
• Design dbt transformation models based on Informatica mappings with best practices.
• Develop dbt native tests and Python unit tests for data quality.
• Create Airflow DAGs to orchestrate Python and dbt end-to-end.
• Contribute to GitLab CI/CD pipelines for dbt and Airflow deployments.
• Perform peer code reviews and troubleshoot SIT/UAT data discrepancies.

Skills

Informatica PowerCenter

dbt Core

Airflow

Python

SQL

Oracle Data Pump

SQL Server BCP

Tools

Oracle Data Pump

SQL Server BCP

Job description

Job Summary

We are currently seeking a Data Migration Engineer to join our team in Bangalore, Karnataka, India.

Role Overview

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.

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.

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
• 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

Preferred

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