Senior/Staff Platform Engineer, Health Plan Data

Senior/Staff Platform Engineer, Health Plan Data What you will do • Build the services and engines that answer the questions. Design, build, and run production APIs and backend services for provider search, eligibility, copay calculation, and claims adjudication support. Own service contracts, SLOs, and on-call for what you ship. Make them multi-tenant, observable, and boring in the best way. • Build the pipelines that feed them. Design and operate batch and streaming pipelines that ingest payor files, API feeds, and event streams: idempotent, replayable, backfill-friendly, with schema validation, quarantine paths, and reconciliation. Choose where scheduled batch, event streaming, and CDC each belong. • Work across the core domains. Take on the hardest problems in health benefits: • Provider network data: rosters, networks, and directories that power accurate care search, including entity resolution across messy, conflicting sources • Eligibility and enrollment: 834 files, census files, and member data that has to be right every cycle, with effective-dated history you can query as of any point in time • Claims: multi-payor claims processing and the data behind adjudication and copay validation • Plan design: benefit configurations and rules that turn a plan document into computable logic • Build enterprise-grade, audit-ready systems. Our customers are regulated payors, and our bar is theirs. You will build for reliability, observability, data quality, and provenance by default: append-only data, versioned config, automated data quality tests, and traceable lineage, in a HIPAA-regulated environment on the path to SOC 2 and HITRUST. • Scale by design, not by headcount. Make onboarding the next payor a configuration exercise, not a rewrite. Build shared services, reusable ingestion frameworks, and platform capabilities that product teams consume rather than rebuild. • Drive outcomes, not output. You are accountable for results: platform reliability, data correctness, delivery. You clear the obstacles in the way, whether or not the code is yours. Partner with product and engineering leadership to turn the roadmap into sequenced, shippable plans. What you will bring • Production experience. 6+ years building and running production systems, with deep expertise in either backend services or data pipelines and real hands-on exposure to the other. • Data pipeline craft. You have built batch and streaming pipelines (Beam/Dataflow, Spark, Pub/Sub or Kafka, or equivalents), and you know how to make them idempotent, replayable, and cheap to backfill. You have used orchestration (Dagster, Airflow, or similar) and a transformation framework (dbt, Dataform, or similar) to build tested, version-controlled data layers. • Data modeling for both worlds. You can model data for analytical use and for low-latency operational serving, including effective-dated and event-sourced patterns, and you know when to use which. • Backend services. You have designed, built, and run APIs and distributed services in production (Python and/or Go, with REST and ideally gRPC). You know your way around Postgres, caching, queues, and the failure modes of each. • Healthcare data. Experience with X12 EDI (834, 837, 835), eligibility, claims, provider data, and/or FHIR, or the appetite to learn it fast. You are comfortable working with PHI under strict data privacy controls, including access controls, de-identification, and audit logging. • Fluency with a modern cloud data stack. GCP preferred (BigQuery, Cloud Run, Cloud Storage) and infrastructure as code. You choose tools pragmatically and can defend the tradeoffs. • AI fluency. You use AI coding tools and agents fluently in your daily work (Claude Code, Cursor, Copilot, or similar) and can show how they have changed the way you design, build, test, and ship. You know how to prompt, give context, break work into agent-sized pieces, and review AI-generated code critically. You have clear, evidence-based opinions about where these tools help, where they fail, and how to keep quality and security high when using them. • Clear communication. Precise writing, async-first habits, and the ability to make complex systems understandable to engineers, product partners, and executives alike. • Nice to have: Experience building or working on ML or agentic systems (tool-using agents, multi-agent workflows, MCP or similar tool integrations, agent evals and observability); health plan or payor-side experience; search and relevance systems; CDC tooling (Debezium, Datastream). Internal Tools/Technology • Cursor / Linear / GitHub / Notion / Whimsical • Slack / Google Workspace / Zoom • incident.io / Sentry • Claude, ChatGPT, Gemini - we are an AI-forward engineering team • macOS / Linux Compensation The target base salary range for this position is $180,000 - $225,000 and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by several factors, including experience, skills, location, internal pay equity, and other relevant business considerations. Benefits/Offerings • Base salary + bonus + equity • Unlimited PTO (mandatory 12 days) • Computer + home office stipend • 401(k) + matching • Medical, dental, and vision insurance • Autonomy and tons of room for career growth Occasional Travel We meet quarterly as a company. Please note that this is a fully remote opportunity.