Job description

Senior QA Lead – Data Engineering & Analytics Testing Remote (U.S.) | Contract Opportunity | Potential for Long-Term Extension Compensation: $60-$70/hour DOE Employment Type: W2 Contract Only Eligibility: No Corp-to-Corp (C2C), Third-Party Vendors, or Subcontractors About the Opportunity Join a globally recognized retail and mobility organization undergoing a large-scale enterprise data transformation. This position will support a strategic Data Platform modernization initiative focused on migrating and validating critical business data across modern cloud-based platforms. We are seeking a Senior QA Lead – Data Engineering & Analytics Testing to drive quality assurance efforts across data engineering and analytics projects. This role is heavily focused on backend data testing (85-90%), including ETL/ELT validation, data reconciliation, transformation testing, and data quality assurance. This is a unique opportunity to join a new project pod from inception, helping define testing strategy, validation frameworks, and quality standards while providing leadership to a small team of QA professionals. What You'll Be Doing Data Validation & Quality Assurance Lead testing efforts for enterprise data engineering and analytics initiatives. Validate complex data transformations, calculations, aggregations, and business rules. Perform end-to-end ETL/ELT testing, including source-to-target reconciliation. Ensure data integrity across cloud-based platforms and large-scale migration efforts. Validate data across Bronze, Silver, and Gold layers within Medallion Architecture environments. Develop and execute SQL-based test cases against large and complex datasets. Build and maintain cross-system data reconciliation processes using source-to-target mappings. QA Strategy & Leadership Define and execute comprehensive testing strategies, plans, and test cases. Establish quality standards and QA best practices across projects. Review test cases, Jira tickets, and defect documentation for quality and completeness. Mentor and guide junior QA team members. Ensure edge cases and complex business scenarios are adequately tested before release. Partner with Data Engineers, Architects, Product Owners, Scrum Masters, and Business Analysts throughout the development lifecycle. Automation & Continuous Improvement Support the transition from manual testing toward automated testing capabilities. Help design and implement reusable automation frameworks for data validation. Contribute to automation initiatives leveraging modern tools and Snowflake-native capabilities. Participate in Agile ceremonies, sprint planning, reviews, retrospectives, and daily standups. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. 7+ years of experience in: Quality Assurance Data Warehouse Testing ETL/ELT Testing Data Quality Validation Strong hands-on experience with: Snowflake SQL Databricks Azure Data Factory (ADF) Azure Data Lake Advanced SQL skills with the ability to independently write and execute test queries. Extensive experience with data reconciliation and source-to-target validation. Experience validating complex business rules and data transformations. Strong understanding of data warehousing concepts and modern cloud data platforms. Experience working within Agile/Scrum environments. Excellent analytical, troubleshooting, and problem-solving skills. Preferred Qualifications Previous QA Lead or Test Lead experience. Python and PyTest automation experience. Experience building or supporting test automation frameworks. Experience with Streamlit or similar automation and workflow platforms. Knowledge of Snowflake Data Quality Monitoring and Data Metric Functions (DMFs). Exposure to Power BI or reporting validation. Experience with Azure DevOps and CI/CD pipelines. Knowledge of Data Governance and Data Quality frameworks. Experience supporting enterprise data migration initiatives. Leadership Expectations This role is approximately: 70% Hands-On Individual Contributor 30% Team Leadership You will: Lead and mentor 2-3 junior QA professionals. Review testing artifacts and ensure quality standards are met. Provide guidance on defect management and validation approaches. Serve as the senior QA authority for your project team. Participate in business-facing discussions and support release readiness activities. What Makes a Strong Candidate? Successful candidates typically have experience with: Snowflake Testing Data Warehouse Testing ETL/ELT Validation Data Quality & Reconciliation Testing Source-to-Target Mapping Validation SQL & Database Testing Data Migration Projects Automation Framework Development QA Leadership & Mentoring Work Environment Fully remote position within the United States. Team operates on Eastern Time. Daily collaboration begins around 8:00 AM ET. Candidates outside Eastern Time must be able to support the team schedule. Strong communication and collaboration skills are essential in this highly visible role. Why Consider This Opportunity? Join a major enterprise data modernization initiative from the ground floor. Work on large-scale cloud data platforms and migration programs. Gain visibility with Data Engineering, Architecture, and Analytics leadership. Long-term engagement with an expected initial duration of approximately 18 months. Strong potential for extension based on project needs and performance. Opportunity to influence quality standards for business-critical data platforms used at global scale. If you have deep experience in Snowflake testing, SQL, ETL/ELT validation, and data quality assurance and are ready to lead while remaining hands-on, we'd love to speak with you.

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