Senior Data QA Engineer

About the Role

We are seeking a Senior Data QA Engineer to own and elevate data quality across our data platforms and client solutions. In this role, you will lead complex data validation efforts, shape testing strategies, and act as a trusted partner to Engineering, Product, and Operations. You’ll set standards for data quality, drive automation, and help ensure the delivery of reliable, production‑grade data solutions at scale.

Your Day to Day

• Lead data quality strategy and execution across multiple projects and datasets.
• Partner closely with Engineering, Product, Operations, and Project Management to influence data design and quality outcomes early in the lifecycle.
• Perform advanced data analysis and validation on large‑scale, client‑specific and healthcare datasets.
• Design, execute, and review complex test plans and test cases, including automated and manual testing approaches.
• Identify systemic data quality risks, drive root‑cause analysis, and partner with teams through resolution.
• Define, refine, and document QA standards, best practices, and verification protocols.
• Mentor junior QA engineers and provide guidance on testing methodologies and data validation techniques.
• Contribute to continuous improvement of QA processes, tooling, and workflows.

What You Bring to the Team

• Bachelor’s degree in Computer Science, Health Science, or a related field (or equivalent practical experience).
• 5+ years of experience in data quality, data QA, or testing roles within data‑driven environments; healthcare experience strongly preferred.
• Advanced SQL skills with the ability to validate, troubleshoot, and reason about complex datasets.
• Strong understanding of data pipelines, integrations, and large‑scale data systems.
• Experience working with healthcare data domains such as enrollment, claims, and provider data.
• Demonstrated ability to lead QA efforts, influence cross‑functional teams, and operate with a high degree of ownership.
• Excellent analytical, problem‑solving, and prioritization skills in fast‑moving environments.
• Strong communication skills, with the ability to explain data quality issues and risks to both technical and non‑technical stakeholders.
• Deep understanding of QA methodologies, testing frameworks, and best practices.