Description
As a Senior Data QA Engineer, you will play a key role in ensuring the accuracy, integrity, and reliability of enterprise data solutions.
Working closely with Data Engineering, Analytics, and business stakeholders, you will validate complex data workflows, drive data quality best practices, and help deliver trusted data that powers critical business decisions.
You will also leverage modern AI-powered tools to enhance testing efficiency, analysis, and overall quality outcomes.
Key Responsibilities
- Review and analyze business, functional, technical, and data requirements.
- Design, develop, and execute test plans, test cases, and test scripts.
- Validate ETL/ELT pipelines, data transformations, and data warehouse solutions.
- Perform manual and automated testing across data platforms and reporting environments.
- Conduct SQL-based data validation, reconciliation, and root cause analysis.
- Identify, document, track, and verify defects through resolution.
- Collaborate with Data Engineers, Developers, Product Managers, and business stakeholders to ensure high-quality releases.
- Create and maintain QA documentation, test evidence, and status reports.
- Mentor and support junior QA team members while promoting quality best practices.
- Leverage AI-powered tools to improve testing productivity and quality.
- Contribute to test automation and continuous improvement initiatives.
Qualifications
- Bachelor's degree in computer science, Computer Engineering, Information Systems, or a related field.
- 4+ years of experience in Data Quality Assurance, Data Testing, or Quality Engineering.
- Strong hands-on experience with SQL and databases such as Snowflake, Redshift, SQL Server, MySQL, or PostgreSQL.
- Experience testing data warehouses, ETL/ELT pipelines, and large-scale data platforms.
- Familiarity with cloud environments such as AWS, Azure, or GCP.
- Experience with defect tracking and test management tools such as Jira or Azure DevOps.
- Exposure to AI-powered tools and technologies, including the effective use of AI assistants and prompt engineering to enhance testing, analysis, and productivity.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management abilities.