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.

Experience
5-9 yrs