Healthcare Generalist AWS Data Engineer

Job Title: Healthcare Generalist AWS Data Engineer

Location: 100% Remote (U.S. Only No California) and Work Hours: EST Business Hours
Duration: 6-12+ Months
Rate: $Market/Hour

11. Medical Imaging & AI/ML Data Processing: Years

Required Skills:
• Data engineering: Production-grade pipeline code, not notebooks. Strong testing discipline with developing deterministic, idempotent, re-runnable jobs.
• AWS data stack: Deep hands-on experience with S3 (layout design, lifecycle policies, storage class economics at image scale), AWS Glue and/or Spark on EMR, Athena, Step Functions, Lambda, and AWS Batch.
• SQL and data modeling: Complex temporal joins, point-in-time correctness, and the discipline to avoid label leakage in time-series clinical data.
• Data quality and lineage: Validation frameworks, schema enforcement, and versioned datasets.
• AWS security and governance: IAM policy design, KMS, VPC endpoints and Private Link, and working inside a HIPAA-eligible architecture with a BAA in place.

Desirable Skills:
• Healthcare data formats and standards: DICOM, FHIR, HL7v2, OMOP CDM, and the practical realities of clinical coding (ICD, LOINC, RxNorm, SNOMED).
• Medical imaging handling: pydicom, OpenSlide, and the basics of WSI pyramid structure and tiling.
• Infrastructure as code (Terraform) development.
• Containerization and CI/CD: Docker, ECR, and a mainstream CI system.
• Enough familiarity with LLM APIs and multimodal payload construction.

Nice to Have:
• Prior work on clinical prediction models or healthcare ML datasets (MIMIC, eICU, or equivalent institutional data).
• Experience with AWS Health Imaging or Health Lake.
• Familiarity with de-identification tooling and re-identification risk assessment.