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Biomedical Data Engineer Jobs in California (NOW HIRING)

Biomedical Specialist

West Hollywood, CA ยท On-site

$70 - $90/hr

... data and GMP documents under minimal supervision. * Investigates EM action level excursions and ... Bachelor's Degree in biology, biochemistry, or related science or engineering specialization.

D.) in physics, applied physics, biomedical optics or engineering, or a related discipline ... data. Experience applying multivariate analysis methods such as principal component analysis to ...

This Principal Biomedical Engineer will partner cross functionally to highlight insights from real ... Applies data analysis and statistical methodologies to generate insights on sensor performance ...

This Principal Biomedical Engineer will partner cross functionally to highlight insights from real ... Applies data analysis and statistical methodologies to generate insights on sensor performance ...

... engineering services, hospital bed and gurney support, healthcare staffing, regulatory readiness ... Ability to read, interpret, and apply a great variety of technical data such as schematic drawings ...

... engineering services, hospital bed and gurney support, healthcare staffing, regulatory readiness ... Ability to read, interpret, and apply a great variety of technical data such as schematic drawings ...

... engineering services, hospital bed and gurney support, healthcare staffing, regulatory readiness ... Ability to read, interpret, and apply a great variety of technical data such as schematic drawings ...

... engineering services, hospital bed and gurney support, healthcare staffing, regulatory readiness ... Ability to read, interpret, and apply a great variety of technical data such as schematic drawings ...

... developer of tools to measure single cell and spatial biology. With the launch of new platforms ... handle biomedical data * Experience building a team composed of new hires into new functions and ...

Showing results 41-60

Biomedical Data Engineer information

What is a biomedical data engineer?

A Biomedical Data Engineer is a professional who designs, develops, and maintains systems for collecting, storing, and analyzing biomedical data. They work at the intersection of healthcare and technology, collaborating with researchers, clinicians, and IT specialists to ensure that medical data is accessible, accurate, and secure. Their work supports medical research, diagnostics, and the development of healthcare solutions by leveraging large datasets, machine learning, and advanced analytics. Biomedical Data Engineers often use programming languages, database management, and data processing tools to handle complex health data from various sources.

What are the key skills and qualifications needed to thrive as a biomedical data engineer, and why are they important?

To thrive as a Biomedical Data Engineer, you need strong programming skills (e.g., Python, R), a background in biomedical sciences or bioinformatics, and experience with data modeling and analysis. Familiarity with big data frameworks, cloud platforms, and tools like SQL, Hadoop, and machine learning libraries, as well as relevant certifications, is commonly required. Excellent problem-solving abilities, attention to detail, and effective collaboration with cross-functional teams help you stand out in this role. These skills enable accurate analysis and integration of complex biomedical data, supporting critical healthcare research and innovation.

What are some common challenges faced by biomedical data engineers when integrating clinical data from multiple sources?

Biomedical Data Engineers often encounter challenges related to data heterogeneity when integrating clinical information from diverse sources such as electronic health records, medical imaging systems, and genomic databases. These sources may use different formats, standards, and terminologies, making data cleaning and normalization a complex task. Additionally, ensuring patient privacy and compliance with healthcare regulations adds another layer of complexity. Collaborating with clinicians, data scientists, and IT teams is essential to address these challenges and ensure data is usable for research and decision-making.

What is the difference between Biomedical Data Engineer vs Biomedical Data Analyst?

AspectBiomedical Data EngineerBiomedical Data Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; experience with data engineering toolsBachelor's or Master's in Biology, Bioinformatics, or related fields; proficiency in data analysis and visualization
Work EnvironmentDevelops data pipelines, manages databases, and ensures data infrastructure for research and healthcareAnalyzes datasets, creates reports, and interprets data for research or clinical decision-making
Employer & Industry UsageResearch institutions, biotech companies, healthcare providersHospitals, research labs, biotech firms, healthcare organizations

While both roles work with biomedical data, Biomedical Data Engineers focus on building and maintaining data infrastructure, whereas Biomedical Data Analysts interpret and analyze data to support research and clinical decisions.

What are popular job titles related to Biomedical Data Engineer jobs in California?

For Biomedical Data Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Biomedical Data Engineer jobs in California look for?

The top searched job categories for Biomedical Data Engineer jobs in California are:

What cities in California are hiring for Biomedical Data Engineer jobs?

Cities in California with the most Biomedical Data Engineer job openings:

Infographic showing various Biomedical Data Engineer job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Hybrid job distribution.

Senior Data Engineer (5+ years)

Foresite Labs

San Francisco, CA โ€ข On-site, Remote

$185K - $221K/yr

Full-time

Medical, PTO

Re-posted 25 days ago


Key responsibilities

  • Build and own production data infrastructure, including designing, implementing, and operating data pipelines that ingest and process various data sources.

  • Model and curate high-quality data assets by performing entity resolution, schema design, and quality enforcement across heterogeneous data sources.

  • Support AI-native workflows by building vector infrastructure and structured data interfaces for GenAI agents and LLM orchestrators.


Job description

Foresite Labs is a translational R&D team that derives insights from precision measurement and population-scale biology and genetics to address unmet clinical needs. We use human genetics to systematically dissect and understand human disease biology and develop and critically evaluate therapeutic hypotheses. We engage in translational research, transforming basic insights into therapeutic opportunities. Our work supports drug discovery and company formation, and provides the core around which new ideas are realized and incubated. We offer competitive salaries, excellent benefits, a flexible work environment, and the opportunity to learn from top thinkers in various disciplines. Foresite Labs is headquartered in San Francisco and Boston.ย 

What You'll Do

  • Build and own production data infrastructure. Design, implement, and operate deterministic data pipelines that feedย  intelligence layers; ingest clinical, financial, scientific, and commercial data from REST APIs, XML feeds, and file-based sources into clean, queryable analytical layers; own the full lifecycle: pagination, rate limiting, auth, schema drift, idempotency, retries, monitoring, and alerting.
  • Model and curate high-quality data assets. Perform entity resolution, schema design, and quality enforcement across disparate and heterogeneous data sources; ensure downstream models, agents and dashboards operate on clean and trustworthy data.
  • Support AI-native workflows. Build vector infrastructure (e.g., embeddings, indexing, retrieval) and structured data interfaces that GenAI agents and LLM orchestrators depend on; ensure AI layers have the right data in the right shape at the right time.
  • Uphold high engineering standards and collaborate broadly. Lead code and design reviews, establish testing and observability best practices, and mentor peers; partner with ML engineers, computational biologists, and company founders to translate scientific and business goals into maintainable, and scalable technical solutions.
  • Leverage agentic coding tools (Claude Code, Codex, or similar) to accelerate prototyping, refactoring, and debugging.ย 

What You'll Bring

  • 5+ years of professional data engineering experience designing, building, and operating production pipelines end-to-end - including schema design for analytical workloads, entity resolution across messy real-world sources, and data quality enforcement at the pipeline level.
  • Deep fluency in Python and SQL, writing performant, well-tested data transformation code (dbt or similar), with production experience in pipeline orchestration (e.g., Airflow, Prefect) covering DAG design, scheduling, dependency management, retry/backfill patterns, and alerting.
  • Hands-on cloud data stack experience across AWS or GCP (e.g., managed Postgres, object storage, query engines, serverless ETL) and working knowledge of IAM, networking, and infrastructure patterns; comfortable with Spark or Trino at scale over Parquet/Iceberg. Terraform, CDK, or Pulumi experience is a plus.
  • Exposure to vector databases (Pinecone, pgvector, Weaviate, or similar) with an understanding of how embedding-based retrieval fits into LLM-powered applications.
  • Comfortable building and navigating Unix environments, containers (Docker), and CI/CD pipelines (GitHub Actions or similar).
  • Mindset for rapid and earlystage execution: bias for action, ownership of ambiguous problem spaces, and demonstrated ability to prioritize and wear multiple hats.
  • Strong written and verbal communication skills - comfortable explaining complex ideas clearly to technical and nontechnical partners.

Nice to Have

  • Familiarity with biomedical or life sciences data (e.g., clinical trials, genomics, drug discovery, pharma commercial data).
  • Familiarity with LLM application patterns: prompting, context engineering, tool use, structured outputs, retrieval-augmented generation (RAG).
  • Experience with dashboard/BI tooling (Streamlit, Retool, Metabase, or similar).

Why Foresite Labs

  • Impact. Your code will accelerate discovery and bring novel therapeutics closer to patients and will help AI driven scientific innovation.
  • Autonomy. Small, senior teams give you room to architect and own endtoend solutions without heavy bureaucracy.
  • Learning. Work at the intersection of software, cloud infrastructure, and biology alongside experts in each domain.
  • Flexibility & Benefits. Competitive salary and equity, comprehensive healthcare, generous PTO, and hybrid/remote options aligned to our SF or Boston hubs.
  • Ready to build? Apply today and help us create the software foundation that powers the next generation of companies advancing biotech and scientific innovation.

Location: San Francisco, CA

Salary range: $185,000 - $221,400

Foresite Labs is an equal opportunity employer. We thrive on diversity and collaboration.