Job
Description
Position Summary: We are seeking a highly skilled ETL QA Engineer with at least 6 years of experience in ETL/data pipeline testing on the AWS cloud stack , specifically with Redshift, AWS Glue, S3 , and related data integration tools. The ideal candidate should be proficient in SQL , capable of reviewing and validating stored procedures , and should have the ability to automate ETL test cases using Python or suitable automation frameworks . Strong communication skills are essential, and web application testing exposure is a plus. Technical Skills Required: SQL Expertise : Ability to write, debug, and optimize complex SQL queries. Validate data across source systems, staging areas, and reporting layers. Experience with stored procedure review and validation. ETL Testing Experience : Hands-on experience with AWS Glue , Redshift , S3 , and data pipelines. Validate transformations, data flow accuracy, and pipeline integrity. ETL Automation : Ability to automate ETL tests using Python , PyTest , or other scripting frameworks. Nice to have exposure to TestNG , Selenium , or similar automation tools for testing UIs or APIs related to data validation. Cloud Technologies : Deep understanding of the AWS ecosystem , especially around ETL and data services. Familiarity with orchestration (e.g., Step Functions, Lambda), security, and logging. Health Check Automation : Build SQL and Python-based health check scripts to monitor pipeline sanity and data integrity. Reporting Tools (Nice to have): Exposure to tools like Jaspersoft , Tableau , Power BI , etc. for report layout and aggregation validation. Root Cause Analysis : Strong debugging skills to trace data discrepancies and report logical/data errors to development teams. Communication : Must be able to communicate clearly with both technical and non-technical stakeholders. Roles and Responsibilities Key Responsibilities: Design and execute test plans and test cases for validating ETL pipelines and data transformations. Ensure accuracy and integrity of data in transactional databases , staging zones , and data warehouses (Redshift) . Review stored procedures and SQL scripts to validate transformation logic. Automate ETL test scenarios using Python or other test automation tools as applicable. Implement health check mechanisms for automated validation of daily pipeline jobs. Investigate data issues and perform root cause analysis. Validate reports and dashboards, ensuring correct filters, aggregations, and visualizations. Collaborate with developers, analysts, and business teams to understand requirements and ensure complete test coverage. Report testing progress and results clearly and timely. Nice to Have: Web testing experience using Selenium or Appium. Experience in API testing and validation of data exposed via APIs.
