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Life Sciences Data Engineer Jobs (NOW HIRING)

Incedo Inc

Senior Data Engineer

San Francisco, CA

$124K - $169K/yr

You will serve as the technical lead for a life sciences data platform build , guiding architecture, mentoring offshore engineers, and owning delivery quality across the engagement. Role and ...

Norstella

Senior Life Sciences Knowledge Engineer

$107K - $146K/yr

Norstella is a premier and critical global life sciences data and AI solutions provider dedicated ... The Role: As a Senior Life Sciences Knowledge Engineer at Norstella, you will sit at the ...

Iff

Life Science Data Engineer

Madison, WI · On-site

$115K - $138K/yr

As a Life Science Data Engineer, you will play a key role in advancing digital transformation within microbiology and microbiome research and development. You will partner with scientists ...

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Life Sciences Data Engineer information

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$44.5K

$129.7K

$177.5K

How much do life sciences data engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for life sciences data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are Life Sciences Data Engineers?

Life Sciences Data Engineers are professionals who specialize in collecting, processing, and managing large volumes of scientific and healthcare data. They design and implement data pipelines and databases to support research, drug discovery, genomics, and clinical trials. Their work ensures that researchers and organizations in the life sciences sector have reliable, accessible, and well-structured data for analysis and decision-making. Life Sciences Data Engineers often work with interdisciplinary teams, using their knowledge of both data engineering and biological sciences to advance scientific discoveries.

What are the key skills and qualifications needed to thrive as a Life Sciences Data Engineer, and why are they important?

To thrive as a Life Sciences Data Engineer, you need a solid background in computer science, bioinformatics, and data engineering, often supported by a degree in a related field. Familiarity with programming languages like Python or R, experience with cloud platforms, and knowledge of data pipeline tools such as Apache Spark or SQL are typically required, alongside certifications in relevant technologies. Strong analytical thinking, problem-solving abilities, and effective communication are standout soft skills for this role. These skills ensure the accurate processing and interpretation of complex biological data, enabling valuable insights that drive research and innovation in the life sciences.

What are some common challenges Life Sciences Data Engineers face when working with scientific datasets?

Life Sciences Data Engineers often encounter challenges such as integrating heterogeneous data sources, dealing with large and complex biological datasets, and maintaining data quality and compliance with regulatory standards. Ensuring interoperability between laboratory information management systems (LIMS), electronic health records, and research databases requires meticulous attention to data formats and standards. Additionally, balancing collaboration with bioinformaticians, scientists, and IT professionals is essential to deliver solutions that meet both scientific and technical requirements.

Senior Product Manager, Life Sciences Data Products

Beacon Talent

Atlanta, GA • On-site, Remote

$152K - $158K/yr

Full-time

Posted 11 days ago

Be an early applicant

Job description

Senior Product Manager, Life Sciences Data Products (Applied AI)

Location: U.S. (Remote-first) with optional hub-based hybrid
Employment: Full-time
Level: Senior IC (high ownership)
Start: ASAP / Flexible

Beacon Talent is leading a confidential search for a venture-backed company building an applied AI + data platform that supports life sciences teams (biopharma, medtech, and research organizations) with secure access to real-world clinical datasets and tooling that accelerates discovery and development while maintaining high standards for privacy, quality, and responsible use.

The Role

As Senior Product Manager, Life Sciences Data Products, you will own the strategy and execution for a portfolio of data-driven products used by life sciences customers to find, access, evaluate, and operationalize complex clinical datasets for R&D and clinical development workflows.

This is a hands-on, high-agency role—ideal for a PM who loves ambiguous problem spaces, can translate market signals into crisp product bets, and can partner deeply with engineering and data teams to ship scalable product capabilities.

What You’ll Own

  • Product vision & roadmap: Define the life sciences product strategy, identify the highest-leverage problems, and translate them into a sequenced roadmap with measurable outcomes.

  • Discovery & validation: Run customer interviews, workflow mapping, and opportunity sizing to determine what to build, what to standardize, and what to avoid as one-off services.

  • Scalable data products: Build repeatable “productized” capabilities that improve dataset usability, governance, search/retrieval, cohort building, and downstream analytics readiness.

  • AI-assisted workflows: Partner with technical teams to design automation that reduces friction in data access and analysis (e.g., metadata enrichment, quality signals, dataset packaging, evaluation tooling).

  • Execution leadership: Write requirements, define success metrics, manage tradeoffs, and drive delivery from concept through launch—iterating based on usage and customer outcomes.

  • Cross-functional alignment: Collaborate closely with go-to-market partners to ensure positioning, packaging, and feedback loops inform the roadmap without turning the product into custom projects.

  • Market awareness: Stay current on life sciences R&D and clinical development trends and incorporate them into differentiation and product choices.

What We’re Looking For

Required

  • 5+ years building data products or platforms for life sciences and/or healthcare customers.

  • Strong product discovery muscle: customer interviews, problem framing, prioritization, and roadmap ownership.

  • Technical fluency across data infrastructure, APIs, pipelines, and working concepts in ML-enabled products (no need to code).

  • Track record partnering with engineering and data teams to deliver complex, high-impact product work.

  • Excellent communication—credible with technical teams and clear with non-technical stakeholders.

  • Comfort operating in a fast-moving environment with evolving inputs and limited process.

Nice to have

  • 0→1 product experience or taking early products to scale in a regulated domain.

  • UX/product design sensibility with strong intuition for end-user workflows.

  • Prior experience in analytics, data science, or experimentation.

  • Familiarity with privacy, governance, and quality frameworks for sensitive datasets.

Why This Role

  • Direct ownership of a high-impact roadmap at the intersection of life sciences + data platforms + applied AI

  • Meaningful influence over what becomes productized vs. service-heavy

  • Close collaboration with technical leadership and high visibility across the company

Compensation

Competitive base + equity + benefits. (Exact range varies by level and location and will be shared during the process.)