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Design, build, and maintain scalable data pipelines to ingest and process clinical data from various healthcare sources. Develop data models and schemas while managing EHR migrations and ensuring high data quality and consistency.
Design, build, and maintain scalable data pipelines that ingest, process, and store clinical data from multiple sources.
Develop and iterate on data models and schemas that support efficient querying and reporting.
Integrate data from various sources, including EHRs, lab systems, and other healthcare applications, ensuring data quality and consistency.
Migrate facilities off their incumbent EHR with mapping, reconciliation, and cutover tooling that operators can trust.
You have both built the data infrastructure as well as used it to analyze and interpret data.
Strong TypeScript, or Python and a willingness to work in TypeScript, plus SQL you are proud of.
You have shipped LLM- or ML-backed extraction and built systems to measure and improve its accuracy over time.
You treat a dropped or duplicated record as an incident, not a rounding error.
Healthcare data standards: HL7 v2, FHIR, X12, C-CDA.
Experience with CMS submissions (iQIES, PBJ) or a claims clearinghouse.
Backend
TypeScript, Node, NestJS
Data
PostgreSQL with row-level security, Prisma, pgvector
Frontend
React, Vite, Radix
Infra
AWS (ECS Fargate, RDS, SNS/SQS, Bedrock), Terraform
Quality
Jest, Vitest, Puppeteer acceptance specs, GitHub Actions merge queue
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