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 enables 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.

Onos is well-funded by some of the best healthcare investors and is working with the nation’s largest health plans. Come join a category-defining company and help reimagine healthcare for the better.

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. This role is a hybrid role based in San Francisco, where you'll be expected to work at our office in person 2-3 times a week.

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
• Build an integration framework that makes onboarding each new payer faster and more reliable over time
• 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 At Onos:

• 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
  
  

Tech Stack:

At Onos, we work with a modern tech stack where we continuously evaluate and adopt cutting-edge technologies as we scale.

• Infrastructure/Systems: AWS (ECS, Bedrock, Glue, etc.), Docker, Github Actions, Terraform
• Languages/Frameworks
• Backend: Python, Django, Celery / Celery Beat, django-ninja, django-tenants
• Frontend: NextJS, Typescript, Tanstack Query, Shadcn UI, Zod, Nuqs
• Database/Storage: PostgreSQL (AWS RDS), S3, Clickhouse
• Development Tools: Github, Jira, Claude Code, CoderabbitAI, Tusk
  
  

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
• Hands-on experience integrating with health plan systems and navigating payer data formats including EDI X12, HL7, FHIR, and custom flat files
• 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
  
  

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Compensation Range: $200K - $250K