Benefits Data QA Analyst
About the Role
At Healthee, we transform complex healthcare data into clear, accurate insights that help people understand and use their benefits. We're looking for a Data QA Analyst who is passionate about ensuring the accuracy and integrity of healthcare and benefits data.
In this role, your primary focus will be on analyzing and validating data across various points in our pipeline-from ingestion through to the user-facing experience. You will play a critical role in identifying inconsistencies, validating business logic, and surfacing data quality issues before they impact users. You'll work closely with data engineers, analysts, and product managers to ensure our data meets the highest standards of trust and usability.
This is an ideal role for someone with a strong analytical mindset, a keen eye for detail, and domain experience in healthcare or benefits data.
What You'll Do
What We're Looking For
Why Join Us?
You'll join a collaborative, data-driven team working to make healthcare information more accessible and accurate. Your work will help build confidence in our data products and directly impact how people interact with their healthcare and benefits.
Salary:
For New York City-based hires only: Compensation Range: $60k-$65k annual salary, commensurate with experience, subject to standard withholding and applicable taxes.
About the Role
At Healthee, we transform complex healthcare data into clear, accurate insights that help people understand and use their benefits. We're looking for a Data QA Analyst who is passionate about ensuring the accuracy and integrity of healthcare and benefits data.
In this role, your primary focus will be on analyzing and validating data across various points in our pipeline-from ingestion through to the user-facing experience. You will play a critical role in identifying inconsistencies, validating business logic, and surfacing data quality issues before they impact users. You'll work closely with data engineers, analysts, and product managers to ensure our data meets the highest standards of trust and usability.
This is an ideal role for someone with a strong analytical mindset, a keen eye for detail, and domain experience in healthcare or benefits data.
What You'll Do
- Perform in-depth analysis of healthcare and benefits data to ensure accuracy, completeness, and consistency across systems.
- Monitor and investigate anomalies, discrepancies, and data gaps, escalating issues to the appropriate teams with clear documentation.
- Define and execute manual and semi-automated validation workflows, ensuring that data conforms to product and business expectations.
- Collaborate with cross-functional teams to align on quality expectations and support ongoing data pipeline improvements.
- Work with domain experts to validate healthcare-specific data elements like coverage policies, provider networks, and plan structures.
- Contribute to and maintain data quality dashboards and reports, helping track and communicate quality metrics over time.
- Support incident investigations by providing detailed root cause analyses and recommending preventative actions.
- Document edge cases, known data limitations, and quality guardrails to improve institutional knowledge.
What We're Looking For
- 2+ years of experience in data quality, QA, or data analysis-especially in data-rich or regulated environments such as healthcare or finance.
- Strong SQL skills for querying, profiling, and validating large structured datasets.
- Demonstrated ability to identify data quality issues, analyze patterns, and communicate findings clearly across technical and non-technical teams.
- Familiarity with healthcare or benefits concepts-such as claims, provider directories, cost-sharing, or coverage logic-is highly valued.
- Strong attention to detail, curiosity, and a drive to understand complex systems and edge cases.
- Experience working with cross-functional teams to troubleshoot issues and define quality expectations.
- Nice to Have
- Exposure to healthcare-specific standards and regulatory requirements (e.g., HIPAA, PHI, EDI 837).
- Familiarity with data quality monitoring tools or platforms (e.g., Great Expectations, Monte Carlo, Datafold).
- Basic understanding of ETL/ELT processes and how data flows into user-facing applications.
- Experience creating or contributing to data validation documentation and quality metric reporting.
Why Join Us?
You'll join a collaborative, data-driven team working to make healthcare information more accessible and accurate. Your work will help build confidence in our data products and directly impact how people interact with their healthcare and benefits.
Salary:
For New York City-based hires only: Compensation Range: $60k-$65k annual salary, commensurate with experience, subject to standard withholding and applicable taxes.
Healthee New York, New York, USA Office
Healthee New York Headquarters Office
213W 35th St, New York, NY, United States, 10001
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

