Data Engineer

Responsibilities

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.

Requirements

Requires strong proficiency in TypeScript or Python, SQL, and experience building data infrastructure. Candidates should have experience with LLM or ML-backed extraction and familiarity with healthcare data standards like HL7 or FHIR.

Skills

• TypeScript
• Python
• SQL
• Data Engineering
• Data Pipelines
• EHR Integration
• LLM
• Machine Learning
• PostgreSQL
• Prisma
• AWS
• Terraform
• NestJS
• React
• HL7 v2
• FHIR

Benefits

• Equity

About this role

What you'll work on
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 might be a fit if
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.
Bonus points
Healthcare data standards: HL7 v2, FHIR, X12, C-CDA.
Experience with CMS submissions (iQIES, PBJ) or a claims clearinghouse.
Our stack
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