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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