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Virta Health is reversing metabolic disease through technology, personalized nutrition, and virtual care delivery. The company has raised over $350M and partners with major health plans, employers, and government organizations.
You will own the data engagement platform that transforms partner and internal data into eligibility decisions and member marketing audiences. This role anchors engineering for Member Marketing and Coverage Eligibility systems—critical infrastructure that determines who can access Virta's care and when they hear about it.
Key responsibilities include:
- Design and own data contracts and processing semantics for identity, deployment context, eligibility, audience attributes, deduplication, and field persistence across the data lifecycle.
- Build end-to-end observability and reconciliation explaining how source records become downstream outcomes, including data freshness, filtering, rejected records, deduplication, safe replay, and historical state repair.
- Lead technical discovery and delivery of high-impact work across Member Marketing and Coverage Eligibility, collaborating with Product, data teams, and external partners.
- Translate evolving audience and workflow requirements into reusable platform capabilities, keeping business policy cleanly separated from technical implementation.
- Design for correctness and auditability in regulated workflows, including data provenance, consent controls, rollback, replay, and safeguards against incorrect or cross-customer data use.
- Modernize legacy file-based processes toward well-contracted, event-driven integrations with strong observability, resilience, and security.
- Own systems end-to-end from architecture through operations, driving improvements in reliability, partner experience, and maintainability.
- Apply an experiment mindset using AI-assisted tooling where it improves speed and quality without compromising correctness.
Within 90 days: Days 1–30 focus on learning Virta's data ecosystem, understanding partner interactions, and building stakeholder relationships. Days 31–60 involve shipping production code and proposing targeted improvements using Build-Measure-Learn. Days 61–90 emphasize owning a meaningful workstream, driving architectural discussions, and establishing yourself as a technical thought partner.
Must-haves: Strong backend engineering with a track record of building and operating scalable, reliable production systems (APIs, event-driven architectures, data integrations). Experience designing data-intensive systems where correctness depends on explicit schemas, identity resolution, and increment semantics.
