ETL Testing With Python

Location: Bangalore, India

Experience: 4 to 6 years

Employment Type: Full-Time

Work Mode: Hybrid / On-site (depending on client)

We are looking for a skilled ETL Tester with strong Python scripting skills and 4+ years of hands-on experience in ETL/Data Warehouse testing. The ideal candidate should have experience working with large datasets, validating data pipelines, and automating test cases using Python. The role requires close collaboration with data engineers, analysts, and business stakeholders.

• Understand and analyze ETL requirements, source systems, and target systems.
• Design, develop, and execute test cases for ETL processes and data validation.
• Perform data quality checks and data reconciliation between source and target systems.
• Write and maintain Python scripts to automate data validation and regression testing.
• Validate data transformation logic, data integrity, and business rules.
• Work with SQL queries to validate data extraction, transformation, and loading logic.
• Collaborate with Data Engineers, BI developers, and QA teams to ensure test coverage.
• Log defects, track them to closure, and perform root cause analysis.
• Participate in sprint planning, daily stand-ups, and other Agile ceremonies.

• 4+ years of hands-on experience in ETL/Data Warehouse Testing.
• Strong expertise in Python for writing data validation and automation scripts.
• Proficient in SQL – complex joins, subqueries, window functions, etc.
• Experience with ETL tools such as Informatica, Talend, SSIS, or similar.
• Familiarity with cloud platforms (AWS/GCP/Azure) is a plus.
• Experience in working with large datasets, preferably in a data lake or data warehouse environment.
• Knowledge of data modeling concepts and data warehouse architectures.
• Strong analytical and problem-solving skills.
• Good communication skills and ability to work independently and in a team.

• Experience with version control systems like Git.
• Experience with CI/CD pipelines and test automation frameworks.
• Familiarity with tools like JIRA, TestRail, or similar.
• Exposure to Big Data ecosystems (Hadoop, Spark) is a bonus.