Data Engineer

QA Automation Engineer We are looking for an experienced ETL QA Engineer with strong expertise in SQL, ETL testing, data validation, and Data Warehousing. The ideal candidate will be responsible for ensuring data accuracy, completeness, integrity, and transformation correctness across ETL pipelines. Key Responsibilities: Perform Source-to-Target validation to ensure data completeness and accuracy throughout ETL processes. Validate data transformations, business rules, aggregations, filtering logic, and data type conversions. Perform data quality checks for nulls, duplicates, truncation, and primary/foreign key constraint violations. Develop and execute test plans and test cases based on Source-to-Target Mapping (STM) documents and business requirements. Create detailed defect/bug reports and support issue resolution. Validate data presented in Power BI/Tableau dashboards against the underlying data warehouse. Perform data reconciliation and support ETL test automation using scripting languages. Required Skills: Strong hands-on experience with SQL, including complex joins, subqueries, aggregations, and data comparison queries. Strong understanding of Data Warehousing concepts, including fact/dimension tables, dimensional modeling, star schemas, and snowflake schemas. Experience with ETL tools such as Informatica PowerCenter, Talend, SSIS, AWS Glue, or Azure Data Factory (ADF). Experience validating data completeness, accuracy, integrity, and transformation logic. Knowledge of Python, Shell Scripting, or PowerShell for automation and data reconciliation. Understanding of ERDs, data modeling, normalization, and denormalization. Experience with data profiling and ETL testing methodologies. Key Skills: ETL Testing | SQL | Data Validation | Data Warehousing | Informatica | Talend | SSIS | ADF | AWS Glue | Python | Source-to-Target Testing | Data Quality | Power BI | Tableau Artech