Role & Responsibilities
Validate ETL pipelines, data migrations, and data transformations.
Perform data validation, reconciliation, completeness, and integrity checks.
Write complex SQL queries for large-scale data validation.
Develop Python automation scripts/frameworks for ETL testing.
Automate regression and data quality validation.
Integrate test automation into CI/CD pipelines (Jenkins/Azure DevOps).
Validate cloud-based data pipelines on AWS/Azure.
Debug ETL failures using Unix/Linux logs.
Collaborate with developers, data engineers, and product teams in an Agile workplace.
Perform root cause analysis and ensure high data quality.

Preferred Candidate Profile
58 years of experience in ETL/Data Warehouse Testing.




Strong hands-on experience with SQL and Python.
Experience in ETL validation, data reconciliation, and data quality testing.
Exposure to AWS or Azure data platforms.
Experience with CI/CD tools (Jenkins, Azure DevOps) and Git.
Good understanding of ETL processes and data warehousing concepts.
Knowledge of Unix/Linux for troubleshooting.
Experience in the Retail domain is a solid plus.
Experience with Hadoop, Spark, Databricks, Jira, or TestRail is an added advantage.
Solid analytical, communication, and problem-solving skills.

📌 Data Quality Engineer Bengaluru
🏢 ALTIMETRIK
📍 Bengaluru