QA Engineer Lead

Responsibilities:

• Own and evolve the QA strategy across Candour's data products, ensuring accuracy and reliability of provider data at scale.
• Dig into client-facing data deliverables spreadsheets, accuracy reports, analysis outputs and understand what the data is telling you, not just whether a test passed.
• Participate in product discussions and bring a quality-informed perspective to roadmap decisions, feature scoping, and release planning.
• Build and manage a QA team, including hiring, mentoring, and setting clear standards for how quality is measured and maintained.
• Write scripts and build lightweight automation to reduce manual testing burden, whether that's Python, SQL, shell scripts, or whatever gets the job done.
• Coordinate testing efforts across engineering, data operations, and client delivery teams that often have competing priorities and timelines.
• Develop and maintain test plans, regression suites, and data validation frameworks tailored to a data-heavy product (not just UI testing).
• Work directly with client data and feedback to understand where quality gaps exist and translate that into actionable improvements.

Requirements:

• 5+ years of QA experience, with at least 2 years managing a QA team.
• Strong analytical instincts, you can open a spreadsheet of provider data or an accuracy report from a client and quickly identify what's off.
• Hands-on scripting ability (Python, SQL, Bash, or similar) with a bias toward automating repetitive work.
• Experience working with data products, data pipelines, or analytics-heavy platforms, not just traditional software QA.
• An intuitive sense for what makes a product good, beyond just "does it work".
• Comfort operating across multiple teams with different priorities and communicating tradeoffs clearly.
• Experience with healthcare data is a plus, but not required.
• Experience working with distributed / offshore engineering teams is a plus.