The RoleWe'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
