QA & Testing Lead Analyst

Cigna Healthcare exists to improve lives. Together, with our global workforce, we are committed to making healthcare more affordable, predictable, and simple. As part of our continued growth and transformation, we are investing in modern Quality Engineering practices, automation, and AI enabled testing capabilities to support the delivery of high quality digital solutions for our customers.

We are looking for an experienced Data Services Test Lead to provide technical leadership and oversight of Data Testing activities across Data Services teams.

This role will act as the Data Testing subject matter expert across Data Services, providing guidance on ETL Testing, test automation, test strategy, and quality assurance practices. The role will work closely with Data Testers across multiple Data Services teams to promote consistent testing approaches, review testing and automation practices, challenge ineffective approaches, and help resolve complex Data Testing and Data Quality issues.

A key focus of the role is ensuring robust end to end validation of data throughout the full data lifecycle, helping teams strengthen testing practices and increase confidence in the accuracy, integrity, and reliability of data solutions.

• →Review and challenge testing strategies, requirements coverage, test coverage, and testing approaches to ensure appropriate validation of source data, transformation logic, integrations, business rules, and downstream impacts.
• →Provide technical leadership, guidance, and support to Data Testers and stakeholders on Data Testing approaches, ETL testing practices, quality controls, tooling, automation, and industry best practices.
• →Support teams in resolving complex Data Testing and Data Quality challenges across ETL, Data Integration, Data Warehousing, Data Migration, Reporting, and Analytics solutions.
• →Establish and promote standards for end-to-end data flow testing, source to target validation, data reconciliation, data integrity verification, and regression testing.
• →Perform detailed reviews of ETL testing approaches, SQL validation techniques, source to target mappings, reconciliation methods, and automation solutions to ensure effective and consistent testing practices across Data Services teams.
• →Establish standards for source to target mapping reviews, test data validation, and end to end data integrity verification across Data Services solutions.
• →Drive adoption of Data Testing automation, automated reconciliation, and modern quality engineering practices to improve testing effectiveness and efficiency.
• →Conduct technical reviews of testing approaches, test evidence, automation solutions, reconciliation controls, and quality checks to identify risks, gaps, and opportunities to improve Data Testing effectiveness.
• →Establish standards for defect management, root cause analysis, defect reporting, and continuous improvement activities.
• →Build strong relationships with Product Owners, Engineering Leads, Architects, Scrum Masters, and business stakeholders to understand priorities, address risks, and improve quality outcomes.

• Extensive experience leading ETL, Data Integration, Data Warehouse, and Data Platform testing activities.
• Extensive experience in Data Testing, ETL Testing, Data Quality, or Data Quality Engineering roles.
• Experience validating ETL processes, source to target mappings, transformation logic, data reconciliation, business rules, and end to end data flows, including transaction level validation and downstream system verification.
• Strong SQL skills with experience performing complex data analysis, validation, reconciliation, troubleshooting, and root cause analysis.
• Experience testing Data Warehousing, Data Integration, Data Migration, Reporting, Analytics, and Data Platform solutions.
• Experience reviewing and challenging testing approaches to ensure adequate coverage of data transformations, integrations, downstream impacts, quality controls, and business risks.
• Strong understanding of data lineage, data integrity controls, transaction level validation, and end to end data validation principles.
• Strong understanding of Data Testing methodologies, Data Quality frameworks, and Quality Engineering best practices.
• Experience driving Data Testing automation, automated reconciliation, and quality improvement initiatives.
• Experience defining and implementing Data Testing standards, frameworks, and technical best practices across multiple delivery teams.
• Experience supporting multiple Agile delivery teams and influencing quality outcomes across complex delivery environments.
• Strong stakeholder management, communication, facilitation, and influencing skills.
• Strong analytical, problem solving, risk management, and continuous improvement mindset.

• Experience working within Healthcare, Insurance, Financial Services, or other regulated industries.
• Experience with cloud data platforms and technologies such as Azure Data Factory, Databricks, Snowflake, Synapse, Informatica, Talend, DataStage, dbt, or similar solutions.
• Experience with Data Testing automation frameworks, quality engineering practices, and CI/CD pipelines.
• Experience evaluating emerging technologies, innovation initiatives, and Proof of Concepts.
• Experience leveraging AI enabled solutions to improve Data Testing, analysis, reporting, or Quality Engineering practices.
• Professional certifications in Data Quality, Data Management, Quality Engineering, Testing, Agile, or related disciplines.
• Certifications or recognised training in Artificial Intelligence, Generative AI, Microsoft Copilot, Azure AI, AWS AI, or related AI technologies.