Etl Testing Engineer

Job Description: Senior QA Analyst (Data + AI) (58 Years) Role Summary Looking for a Senior QA Analyst (5–8 years) with strong expertise in data-driven testing, ETL validation, backend validation, and AI-driven automation frameworks. The ideal candidate should be capable of working across application, database, automation, and AI layers, with emphasis on building scalable validation solutions using Python, SQL, and AI tools like Copilot/Cursor. Key Responsibilities • Understand business requirements, data flows, and system architecture • Contribute to test strategy and test planning for applications and ETL pipelines • Perform functional, integration, regression, and data validation testing • Validate large datasets using SQL/Snowflake queries • Perform ETL validation (source-to-target, transformation logic, reconciliation) • Build and maintain Python-based automation scripts and frameworks • Develop and implement AI-assisted automation solutions using Copilot/Cursor/LLMs • Automate data quality checks, anomaly detection, and reporting • Analyze data discrepancies and perform root cause analysis (RCA) • Enhance and optimize automation and validation frameworks • Maintain QA artifacts (test cases, validation queries, reports, AI workflows) Required Skills & Technical Expertise • Strong SQL expertise (joins, window functions, CTEs, performance queries) • Strong Python skills for automation, scripting, and data validation • Hands-on experience with Snowflake / Data Warehouse platforms • Understanding of ETL / ELT workflows, data pipelines, and transformations • Experience with PyTest / Robot Framework or similar • Exposure to Copilot / Cursor / Gen AI tools • Knowledge of prompt engineering and AI-assisted workflows Good to Have • CI/CD integration for automation • Big Data platforms (Databricks, Hadoop) • Cloud platforms (Azure, AWS) • Experience with LLM-based automation or AI tools Qualification Bachelor’s degree in Computer Science / IT or related field.