Data Quality Assurance Manager at Candor Health

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

12 Aug, 26

Salary

0.0

Posted On

14 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

QA Strategy, Team Management, Python, SQL, Bash, Data Validation, Automation Testing, Regression Testing, Analytical Skills, Healthcare Data, Data Pipelines, Test Planning

Industry

Data Infrastructure and Analytics

Description

About Candor Health Candor Health is a healthcare intelligence platform that is powering companies with high quality, transparent, and actionable data in the US on doctors, facilities, insurance plans, costs, and more. We believe that providing higher quality, transparent data not only leads to better decisions, but creates greater trust and confidence for the entire healthcare ecosystem. We are getting data from a variety of growing sources including certification boards, booking sites, claims, social media, and others, with human and automated verification. We have built a high quality data set that has been baked off favorably against other healthcare data vendors, including public companies and startups that have been compiling healthcare data for many years. We are backed by some of the most prominent VCs and angels in healthcare who have a track record of building very successful technology companies. Life at Candor At Candor, everyone is a leader. The areas you own are yours to build and progress. Best ideas win! We value a culture where the team not only enjoys working together solving some of the biggest data challenges in the healthcare industry, but also has fun doing it. Building a great company is hard work but work-life balance is also important. Responsibilities Own and evolve the QA strategy across Candor'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 Qualifications 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

Responsibilities

Own and evolve the QA strategy for data products to ensure the accuracy and reliability of provider data at scale. Build and manage a QA team while developing automation scripts and data validation frameworks.