Lead Engineer (Data/Integrations)
About Onos Health
Onos Health’s mission is simple but ambitious: ensure every healthcare dollar goes toward delivering the highest quality care. Today, 30% of total U.S. healthcare spending is wasted due to ineffective care and administrative burden caused by misalignment between providers and payers. Onos is addressing this by building the largest AI-driven healthcare data platform. Our models enable payers to make faster, more accurate decisions across their populations. By guiding members to the right care, Onos is channeling more dollars to high-quality care that drives better outcomes while making healthcare more affordable.
Why Onos?
Meaningful impact: Help fix what is fundamentally broken in healthcare
Direct collaboration: Work alongside experienced founders with deep healthcare and data expertise
Culture: Join a high-performing, transparent, and results-oriented team
Ownership: Significant responsibility and autonomy from day one
Opportunity: Play a pivotal role in building a fast-growing, category-defining healthcare AI company
The Role
We're seeking an experienced data engineering leader with deep healthcare payer domain expertise who is motivated to meaningfully improve the way healthcare is administered in the country. You'll own the architecture and implementation of our integrations with claims and utilization management systems at the nation's largest health plans. As an early team member, you'll build the data infrastructure that powers the entire Onos platform and establish the best practices for a growing data engineering team.
What you’ll be doing at Onos:
Lead the architecture and implementation of data integrations with major healthcare payers, including claims feeds, utilization management authorization data, eligibility files, and provider rosters
Work across healthcare data formats and exchange methods: EDI X12 (837/835/270/271/278), SFTP, flat files, proprietary APIs, and HL7/FHIR
Build monitoring, reconciliation, and data quality systems, including defining requirements, test scenarios, and acceptance criteria for each integration
Build and scale data pipelines for our AI/ML systems and analytics dashboards for behavioral and mental health quality and cost
Establish engineering best practices and technical foundations for future team growth
Technical Challenges
Build a payer integration framework that makes each new national and regional health plan onboarding faster and more reliable than the last
Develop fault-tolerant data pipelines that process millions of claims records while maintaining strict data quality, security, and compliance requirements
Design normalization layers that translate varied payer data formats into a unified data model for AI/ML and analytics
Architect robust monitoring and alerting systems that detect data quality issues, feed disruptions, and schema drift before they impact downstream systems
Establish best practices for using AI tooling across the engineering workflow to ship faster without sacrificing quality
What we’re looking for:
5+ years experience in data engineering, with significant time spent working with healthcare payer data (claims, UM, eligibility)
Prior experience leading engineering teams as a tech lead or engineering manager
Strong system design skills with a track record of defining clear requirements, test scenarios, and acceptance criteria for complex data systems
Customer obsessed and motivated to make an impact in the healthcare space
A hands-on technical leader who can architect robust and extensible systems, establish best practices with AI coding tools, and ship high quality production code
Bonus points if you have:
Direct experience integrating with claims platforms or UM systems such as QNXT, Facets, Amisys, Jiva, CareRadius, or similar
Experience with behavioral health or mental health claims data (e.g., behavioral health carve-outs, BH-specific CPT codes, quality measurement)
Built data infrastructure that powers AI/ML systems — feature pipelines, training data preparation, model monitoring
Benefits and Perks
Flexible hybrid arrangement: 2-3 days/week at San Francisco office (Financial District), remote-first culture
Unlimited vacation policy
Paid parental leave
Medical, dental, and vision insurance
Pre-tax commuter benefits
401(k)
Significant equity as an early employee
Direct mentorship from experienced founders
Ground-floor opportunity to help build a team and culture
Regular team events and offsites
Company-provided equipment and home office setup
Compensation Range
$200K - $250K