Remote Data Migration Engineer: Informatica to dbt/Airflow

NTT DATA, Inc.; Texas; Hybrid; USD 85,000 - 148,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401k with company match

Paid time off

Flexible spending or HSA

Employee assistance program

Job summary

NTT DATA Services is seeking a Senior Data Migration Engineer (Informatica/DBT) to lead a large-scale migration to a modern data stack. The role emphasizes Python-based EL pipelines, dbt transformations, and Airflow orchestration in a remote US setting.

You will convert complex Informatica workflows to Python/dbt, build robust data pipelines, and ensure production-quality outputs with enterprise-scale performance.

Qualifications

• 5+ years of Informatica PowerCenter experience (mappings, sessions, workflows).
• 3+ years of hands-on dbt Core experience (models, tests, incremental).
• Experience with Airflow DAGs and orchestration.
• 5+ years of Python for data pipelines and batch processing.
• 5+ years of SQL experience with large datasets.
• Experience with Oracle Data Pump or SQL Server BCP for high-volume movement.

Responsibilities

• Translate Informatica workflows into Python EL scripts and dbt models.
• Develop Python EL pipelines to land high-volume data into the warehouse.
• Design dbt transformation models with best practices and tests.
• Create Airflow DAGs to orchestrate end-to-end pipelines.
• Contribute to GitLab CI/CD for dbt and Airflow deployments.
• Perform peer reviews and troubleshoot data discrepancies during SIT/UAT.
• Produce runbooks and technical documentation.

Skills

Informatica PowerCenter

dbt Core

Airflow

Python

SQL

Oracle Data Pump / BCP

Tools

SQLAlchemy

cx_Oracle

pyodbc

Job description

NTT DATA Services is seeking a Senior Data Migration Engineer (Informatica/DBT) to lead a large-scale migration to a modern data stack. The role emphasizes Python-based EL pipelines, dbt transformations, and Airflow orchestration in a remote US setting.

You will convert complex Informatica workflows to Python/dbt, build robust data pipelines, and ensure production-quality outputs with enterprise-scale performance.