Quality Assurance Engineer - ETL/Datawarehouse Testing

Key Responsibilities

• Develop and execute comprehensive test strategies, test plans, and test cases for data pipelines, ETL processes, and analytical systems.
• Validate data transformations, data mapping, and business rules across multiple data sources.
• Perform in-depth data quality checks, including completeness, accuracy, consistency, and integrity.
• Conduct ETL/ELT testing, including source-to-target validation, schema verification, and data reconciliation.
• Work closely with Data Engineers, Developers, and Analysts to understand requirements and ensure end-to-end data accuracy.
• Build and maintain automated data validation scripts and frameworks using SQL, Python, or other relevant tools.
• Test data ingestion, data processing, and data storage across relational and non-relational databases.
• Identify data defects, provide root-cause analysis, and ensure timely resolution.
• Validate performance, scalability, and reliability aspects of data flows and pipelines.
• Work within CI/CD environments to integrate data testing into automated pipelines.
• Document test results, defect logs, and data quality metrics.
• Ensure compliance with data governance, security, and privacy standards.
  

Technical Skills

• Strong hands-on experience with SQL (complex joins, stored procedures, window functions, aggregations).
• Experience in validating large datasets across RDBMS (e.g., SQL Server, PostgreSQL, Oracle) and/or NoSQL systems.
• Experience with ETL testing using tools such as Informatica, Talend, SSIS, ADF, or similar.
• Hands-on experience in writing automated test scripts using Python, PyTest, or similar frameworks.
• Familiarity with data warehousing concepts, star/snowflake schemas, fact/dimension tables.
• Understanding of data pipelines on cloud platforms (AWS, Azure, or GCP).
• Experience with CI/CD tools such as Jenkins, GitLab CI, Azure DevOps, etc.
• Ability to test APIs, data services, and microservices using tools like Postman, Swagger, or automation frameworks.
  

Soft Skills & Behavioral Competencies

• Strong analytical and logical reasoning skills.
• Excellent attention to detail and commitment to data accuracy.
• Ability to collaborate effectively across cross-functional teams.
• Clear and concise communication skills (written & verbal).
• Strong documentation and reporting skills.
• Ability to work independently and drive tasks to completion.