Informatica & Python ETL Engineer | Data Quality & Testing

Infosys Limited; Raleigh (NC); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Long-term/Short-term Disability

Health and Dependent Care Reimburse- m

Insurance (Accident, Critical Illness,

401(k) plan

Job summary

Infosys Limited in the USA seeks an Informatica Python ETL Data Engineer & Tester to design, develop, test, and validate ETL pipelines across data warehousing environments. The role requires Python, SQL, Oracle, and AWS experience, with emphasis on data quality and automation.

You will collaborate with business and data engineering teams, participate in end-to-end SDLC, and contribute to data migration testing and release readiness.

Qualifications

• Informatica development, Python, AWS, SQL, Oracle, and GitLab.
• ETL Testing, Data Warehouse Testing, and Data Migration Testing.
• Python-based ETL and data test automation for source-to-target validation and regression testing.
• SQL query writing and Oracle database validation.

Responsibilities

• Document requirements and guide design discussions to inform development teams.
• Code review and maintain code repositories; implement new features.
• Develop and execute test strategies; analyze results and coordinate bug fixes.
• Create user training, documentation, and support materials for new apps.
• Resolve production issues and implement preventive measures for reliability.
• Maintain records of code, tests, and testing processes.

Skills

Python

SQL

Oracle

AWS

GitLab

ETL Testing

Data Warehouse Testing

Data Migration Testing

Shell scripting

Python-based ETL testing

Education

Bachelor’s degree

Tools

Autosys

Control-M

Airflow

Job description

Infosys Limited in the USA seeks an Informatica Python ETL Data Engineer & Tester to design, develop, test, and validate ETL pipelines across data warehousing environments. The role requires Python, SQL, Oracle, and AWS experience, with emphasis on data quality and automation.

You will collaborate with business and data engineering teams, participate in end-to-end SDLC, and contribute to data migration testing and release readiness.