About Cigna
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.
The Position
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.
Key Responsibilities
- 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.
Required Skills and Experience
- 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.
Desirable Skills and Experience
- 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.
About The Cigna Group
Cigna Healthcare, a division of The Cigna Group, is an advocate for better health through every stage of life. We guide our customers through the health care system, empowering them with the information and insight they need to make the best choices for improving their health and vitality. Join us in driving growth and improving lives.Skills Required
- 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.
- Experience validating ETL processes, source-to-target mappings, transformation logic, reconciliation, business rules, and end-to-end data flows.
- Strong SQL skills for 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 testing approaches for coverage of transformations, integrations, downstream impacts, controls, and business risks.
- Strong understanding of data lineage, data integrity controls, transaction-level validation, and end-to-end data validation.
- Strong understanding of data testing methodologies, data quality frameworks, and quality engineering 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 in complex delivery environments.
- Strong stakeholder management, communication, facilitation, and influencing skills.
- Strong analytical, problem-solving, risk-management, and continuous-improvement skills.
- Experience in healthcare, insurance, financial services, or another regulated industry.
- Experience with cloud data platforms such as Azure Data Factory, Databricks, Snowflake, Synapse, Informatica, Talend, DataStage, dbt, or similar.
- Experience with data testing automation frameworks, quality engineering practices, and CI/CD pipelines.
- Experience evaluating emerging technologies, innovation initiatives, and proofs of concept.
- Experience using AI-enabled solutions to improve data testing, analysis, reporting, or quality engineering.
- Professional certifications in data quality, data management, quality engineering, testing, Agile, or related disciplines.
- Certifications or recognized training in artificial intelligence, generative AI, Microsoft Copilot, Azure AI, AWS AI, or related technologies.
Cigna Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cigna and has not been reviewed or approved by Cigna.
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Strong & Reliable Incentives — Strong bonus outcomes are frequently highlighted, with annual bonuses described as really good alongside above-average salary levels. Stock or long-term incentive elements are also noted as part of the overall package in some roles.
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Leave & Time Off Breadth — Time-off benefits are portrayed as a meaningful part of total rewards, including generous PTO and flexibility that can enhance the perceived value of compensation. Flexible work-from-home arrangements are repeatedly linked with satisfaction about the overall package.
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Healthcare Strength — Health coverage is described as broad in design, with preventive care often covered at no charge in-network and options like virtual care and wellness incentives. A large provider network and strong digital tools are positioned as practical advantages when using benefits.
Cigna Insights
What We Do
At Cigna, we're more than a health insurance company. We are your partner in total health and wellness. And we’re here for you 24/7 – caring for your body and mind. As a global health service company, Cigna's mission is to improve the health, well-being, and peace of mind of those we serve by making health care simple, affordable, and predictable. Our values are the core of our culture. Our values guide how all 74,000 of us around the world work together, serve our customers, patients, clients, communities, and deliver on our mission.
