Job Description

Healthcare Data Engineer

San Francisco - Hybrid (2 days/week in office)

$140,000 - $170,000 Salary + Private Equity

The Company:

Our client is a biotech company focused on delivering actionable genetic insights through advanced sequencing and intuitive digital platforms. The team combines engineering, data science, and healthcare expertise to develop cutting-edge solutions.

The Role:

As a Healthcare Data Engineer you will design, build, and scale data pipelines that powers their disease prediction platform. You’ll be at the forefront of harmonizing diverse EHR datasets, ensuring clinical data is standardized, interoperable, and research-ready. This hands-on role requires deep experience with ETL workflows, clinical ontologies like HL7 FHIR and OMOP, and the ability to collaborate across clinical, bioinformatics, product, and engineering teams. If you're passionate about applying modern data engineering practices to improve patient outcomes, we’d love to meet you.

Responsibilities:

• Standardize clinical data using formats like HL7 FHIR, OMOP, SNOMED, ICD-10, and LOINC to ensure interoperability.
• Build and maintain ETL pipelines to ingest, de-identify, and unify data from various EHR systems, including structured and unstructured sources.
• Support a scalable cloud infrastructure for large-scale data processing using tools like Spark and Databricks.
• Ensure data privacy and compliance with HIPAA, GDPR, and related regulations.
• Monitor data quality with automated checks and anomaly detection systems.
• Collaborate with cross-functional teams (engineering, product, clinical, bioinformatics) to align on goals and deliver research-ready data.

Required Qualifications

• Direct experience working with EHR data , biobank records, or clinical data platforms.
• Strong skills in Python and SQL , with a proven track record working in cloud environments like AWS, GCP, or Azure.
• Solid foundation in building and refining ETL pipelines , including experience managing data warehouses.
• Experience building data pipelines that power ML features —especially for healthcare use cases like anomaly detection.
• Familiarity with clinical data standards and coding systems such as HL7 FHIR, OMOP, UMLS, ICD, SNOMED, LOINC, or RxNorm.

Think you're a great fit? Please email [email protected] with the following information!:

1. Current Resume (no more than 2-3 pages)
2. Current location
3. Experience with Healthcare Data
4. Timeline to start a new role
5. Upcoming Availability for a 15-20 minute phone call

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