We are looking for an experienced ETL Test Engineer to validate data pipelines, data warehouses, and reporting layers. You will ensure data is accurate, complete, and consistent as it moves from source systems to targets, working closely with data engineers, BI developers, and business analysts.

Analyze business requirements, source-to-target mapping (STM) documents, and data models to design test strategies, test plans, and test cases Perform end-to-end ETL testing: source validation, transformation logic, data loads (full and incremental), and target validation Write complex SQL queries to validate row counts, data completeness, duplicates, nulls, referential integrity, and business rules Validate SCD (Type 1/2) logic, aggregations, joins, lookups, and data type and schema changes Test data warehouse, data mart, and data lake pipelines across batch and near-real-time loads Verify reports and dashboards (Power BI, Tableau, Cognos) against warehouse data Perform data reconciliation, data profiling, and data quality checks Raise, track, and retest defects in Jira/ALM, and perform root cause analysis with developers Build automated data validation scripts/frameworks using Python, SQL, or tools such as Great Expectations, dbt tests, or QuerySurge

5-10 years of experience in ETL / Data Warehouse testing Strong SQL skills (joins, subqueries, window functions, CTEs, analytical functions) on Oracle, SQL Server, Teradata, PostgreSQL, or similar Hands-on experience with at least one ETL tool: Informatica, Talend, SSIS, DataStage, ODI, or cloud tools like Azure Data Factory, AWS Glue Solid understanding of data warehousing concepts: star/snowflake schema, fact and dimension tables, SCD, staging, ODS Experience writing test cases from STM documents and performing data reconciliation Familiarity with test management and defect tools: Jira, HP ALM, Xray, TestRail Understanding of SDLC, STLC, and Agile methodologies Strong analytical, debugging, and problem-solving skills