We are looking for an ETL QA Engineer with strong experience in data warehouse testing, ETL/ELT validation, and Snowflake. The role involves ensuring data accuracy, integrity, and completeness across data pipelines and analytics platforms. The ideal candidate should have hands-on expertise in SQL-based data validation, ETL testing, and Snowflake environments, along with a strong understanding of data flows and transformation logic.

• Perform ETL/ELT testing for data pipelines, ensuring accurate data movement from source to target systems. • Validate data transformations, business rules, aggregations, and mappings across staging and reporting layers. • Execute data validation and reconciliation using SQL queries. • Work on Snowflake data platform, validating data loads, transformations, and performance. • Perform end-to-end testing including source-to-target validation and data completeness checks. • Collaborate with data engineers, analysts, and business teams to understand requirements and define test cases. • Execute functional, regression, and integration testing for data systems. • Identify, log, and track defects; perform root cause analysis. • Support UAT cycles and release validation. • Contribute to test automation where applicable using tools like QuerySurge or Python.

• 4–6 years of experience in ETL / Data Warehouse Testing / Data QA. • Hands-on experience with Snowflake. • Strong proficiency in SQL for data validation and analysis. • Good understanding of ETL/ELT processes, data pipelines, and data warehousing concepts. • Experience in data reconciliation, data profiling, and validation techniques. • Familiarity with data integration tools such as Informatica, Talend, or Azure Data Factory. • Experience in API/file-based data validation is a plus. • Knowledge of Agile / Scrum methodology. • Strong analytical and problem-solving skills.