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Data Engineer (Generative AI & Healthcare Data)

Altarum · United States · US

Clinical Data Science
Remote
physician
Demand86
Career growth84
Healthcare fit38
Remote potential70
Salary band
USD 145k – 175k
5-year outlook
Data engineering combined with generative AI and healthcare interoperability skills is a durable, well-compensated niche; nonprofit and public-sector pay typically sits below commercial big tech but grows steadily with progression to senior, principal, or AI engineering roles. Exact figures vary by location and clearance requirements.
Clinical license
Not required
Applicant reach
narrow
Seniority
mid
Employment type
full-time
Date found
2026-10-02

Intelligence details

Flexible work details

Side income
Classified as side-income friendly
Engagement type
Contract
Hours
Variable hours
Eligible countries
United States
Profession fit
physician
Rate period
Annual

Why this was classified this way

  • contract

Listing via Himalayas.

Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.

Why this is worth applying to

Worth applying only if you already have real Python/SQL/cloud data engineering experience, ideally with healthcare data exposure — clinicians without a technical portfolio will likely be screened out. For clinical-informatics-trained professionals, it is a strong, mission-driven pivot into healthcare AI infrastructure.

Who should apply

Physicians, nurses, or pharmacists with clinical informatics training and hands-on Python/SQL/cloud experience; healthcare data analysts or BI developers ready to move into data engineering; IMGs or healthcare graduates with a computer science or engineering background; public health graduates with pipeline and Databricks/Spark experience.

CV angle

Lead with concrete engineering evidence — Python and SQL code, pipeline ownership, cloud (AWS/Azure) deployments, CI/CD, and Databricks/Spark work — then layer healthcare domain credibility: EHR data extraction, FHIR/HL7 interfaces, claims or registry datasets, SDOH or quality-measure data, and any informatics or QI projects where you built or maintained data models. Quantify pipeline scale, data quality improvements, and reliability outcomes rather than clinical duties.

Skills to highlight

  • Python and SQL production development
  • Data pipeline / ELT design and orchestration
  • Cloud platforms (AWS, AWS GovCloud, Azure, Azure Government)
  • Databricks, Spark/PySpark, Delta Lake, dbt
  • Healthcare interoperability standards (FHIR R4, US Core, HL7 v2)
  • CI/CD, infrastructure as code, and automated testing
  • Data quality, lineage, monitoring, and incident response
  • Retrieval-augmented generation, embeddings, and vector search

Role summary

A mid-level data engineering role at public-health nonprofit Altarum, building and operating cloud data platform components, healthcare data pipelines, and production generative AI applications. The engineer owns ingestion and transformation of Medicaid/Medicare claims, FHIR and HL7 data, and other public health sources, plus RAG and document-intelligence applications, with responsibility for CI/CD, data quality, reliability, and cost optimization.

We publish our own intelligence summary, never the full job description. Always confirm details with the employer when you apply.