Senior Data Quality Analyst

Komodo Health • New York, NY

3d • Hybrid

About The Position

Komodo Health is seeking a Senior Data Quality Analyst to ensure the accuracy and reliability of their Healthcare Map and AI-driven products. This role is crucial for maintaining data quality as the company scales. The analyst will act as an independent voice, verifying that data outputs are not only technically sound but also analytically correct and valuable to customers. The position involves rigorous analysis, investigation of issues, and preparation for weekly data release reviews, contributing to Komodo's mission to reduce the global burden of disease.

Requirements

• 6+ years of experience in data quality, data analysis, or analytics engineering, preferably in healthcare, life sciences, or another domain with complex, multi-source data.
• Strong SQL skills for large-scale analysis (joins, window functions, aggregations, tracing data lineage). Snowflake preferred.
• Proven ability to work through ambiguous issues from signal to root cause.
• Experience designing or executing pre/post release testing, including defining attributes, tolerances, and escalation criteria.
• Familiarity with claims data (medical, pharmacy, enrollment) and common quality patterns and failure modes.
• Ability to leverage AI tools (Gemini, Claude, Cursor, etc.) to enhance personal productivity, streamline workflows, and content and visualization creation.

Nice To Haves

• Comfortable using Python for analysis, validation, and light automation—able to read and adapt existing scripts.

Responsibilities

• Independently assess whether Komodo’s data outputs are analytically sound, ensuring the data tells the right story for customers.
• Design and run pre/post-release comparisons across key attributes (patient counts, claim volumes, fill rates, deduplication, payer attribution, provider coverage).
• Surface and document issues missed by automated tests, such as demographic shifts, volume changes, or rule edge cases.
• Assess each issue, determine customer impact, and recommend action (approve, conditional approve, hold, or escalate).
• Track what was tested, what passed, and accepted risks for each release, creating an auditable quality trail.
• Review and prioritize DPQ Jira issues, distinguishing data output problems, pipeline failures, and cases needing joint investigation.
• Query Snowflake to trace anomalies to source, validate against expectations, and rule out alternatives.
• Produce clear reports outlining the issue, evidence, likely cause, and next steps for both technical and non-technical audiences.
• Partner with Data Engineering and Architects to drive resolution and verify fixes address the root issue.
• Compile a weekly record of data pipeline execution status, anomalies, and comparisons against expected behavior.
• Document which quality checks were expected and executed for each pipeline, surfacing any gaps in coverage.
• Aggregate all quality issues raised during the week into a single structured view with status, severity, and recommended disposition.
• Prepare the DPQ release recommendation document for the weekly publication meeting.

Benefits

• Comprehensive health, dental, and vision insurance
• Flexible time off and holidays
• 401(k) with company match
• Disability insurance
• Life insurance
• Leaves of absence in accordance with applicable state and local laws and regulations and company policy
• Performance-based bonuses
• Equity awards

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed