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Bioinformatics Data Engineer Jobs (NOW HIRING)

Design, develop, and maintain scalable bioinformatics pipelines for NGS data analysis, including ... Engineering Practices * Write production-grade code using Git-based workflows, peer review, testing ...

Our scientists, engineers, sales executives, and visionaries are united by an unwavering commitment ... Perform analysis of clinical bioinformatics data while maintaining low turnaround time for data ...

Bioinformaticist

Washington, DC · On-site

$99K - $225K/yr

Experience in bioinformatics, data engineering, or biological data pipeline development * Experience with NoSQL for large-scale genomic datasets * Experience with containerization and orchestration ...

Bioinformaticist

Mclean, VA · On-site

$99K - $225K/yr

Experience in bioinformatics, data engineering, or biological data pipeline development * Experience with NoSQL for large-scale genomic datasets * Experience with containerization and orchestration ...

Bioinformaticist

Mclean, VA · On-site

$99K - $225K/yr

Experience in bioinformatics, data engineering, or biological data pipeline development * Experience with NoSQL for large-scale genomic datasets * Experience with containerization and orchestration ...

OR

$122.40K - $161.30K/yr

Natera is seeking an experienced Senior Software Engineer with modern data engineering and AI ... Apply domain knowledge in genetics and bioinformatics to design data models, schemas, and ...

Experience in bioinformatics, data engineering, or biological data pipeline development * Experience with NoSQL for large-scale genomic datasets * Experience with containerization and orchestration ...

Experience in bioinformatics, data engineering, or biological data pipeline development * Experience with NoSQL for large-scale genomic datasets * Experience with containerization and orchestration ...

Bioinformaticist

Reston, VA · On-site

$99K - $225K/yr

Experience in bioinformatics, data engineering, or biological data pipeline development * Experience with NoSQL for large-scale genomic datasets * Experience with containerization and orchestration ...

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Bioinformatics Data Engineer information

See salary details

$43K

$131.1K

$238.5K

How much do bioinformatics data engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for bioinformatics data engineer in the United States is $131,053.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,000.00 and $157,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Bioinformatics Data Engineer, you need a strong background in computer science, biology, and statistics, often supported by a relevant degree and experience in data engineering. Proficiency with programming languages (such as Python, R, or SQL), bioinformatics tools, cloud platforms, and big data frameworks (like Hadoop or Spark) is typically required. Strong problem-solving, collaboration, and communication skills help you work effectively across interdisciplinary teams and convey complex findings. These skills ensure accurate analysis, efficient data pipeline development, and meaningful insights that advance biological research and healthcare solutions.

How do Bioinformatics Data Engineers typically collaborate with researchers and other teams in a biomedical organization?

Bioinformatics Data Engineers often work closely with biologists, data scientists, and software engineers to ensure the effective collection, processing, and analysis of complex biological data. They regularly participate in cross-functional meetings to understand research goals, develop data pipelines, and troubleshoot data-related issues. Collaboration is essential, as engineers must translate scientific requirements into technical solutions, provide data access and visualization tools, and support researchers in extracting meaningful insights from large datasets. This teamwork fosters a dynamic environment where communication and adaptability are key.

What is a Bioinformatics Data Engineer?

A Bioinformatics Data Engineer is a professional who designs, develops, and maintains data infrastructure for managing and analyzing large-scale biological data, such as genomics or proteomics datasets. They build pipelines and tools to process, store, and retrieve complex biological information efficiently. Their work enables researchers and scientists to access and interpret data for discoveries in fields like medicine, genetics, and biotechnology. Often, they collaborate closely with bioinformaticians, data scientists, and software engineers to support research initiatives.

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

AspectBioinformatics Data EngineerBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fields; programming skillsBachelor's or Master's in Bioinformatics, Biology, or related fields; data analysis skills
Work EnvironmentData pipelines, database management, software developmentData interpretation, report generation, biological data analysis
Employer & Industry UsageBiotech companies, research labs, pharmaResearch institutions, healthcare, biotech
Common Search & ComparisonFocuses on data infrastructure and pipelinesFocuses on biological data interpretation

The main difference between a Bioinformatics Data Engineer and a Bioinformatics Analyst lies in their focus areas. Data Engineers build and maintain data pipelines and infrastructure, while Analysts interpret biological data to generate insights. Both roles require strong bioinformatics knowledge, but Data Engineers emphasize programming and data management, whereas Analysts focus on biological interpretation and reporting.

More about Bioinformatics Data Engineer jobs
What cities are hiring for Bioinformatics Data Engineer jobs? Cities with the most Bioinformatics Data Engineer job openings:
What states have the most Bioinformatics Data Engineer jobs? States with the most job openings for Bioinformatics Data Engineer jobs include:
Infographic showing various Bioinformatics Data Engineer job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $131,053 per year, or $63 per hour.
AI & Informatics Engineer

AI & Informatics Engineer

Prime Medicine

Cambridge, MA • On-site

Other

Posted 15 days ago


Job description

Role Summary

Prime Medicine is seeking an AI & Informatics Engineer to join our AI Foundry and support our pipeline delivery.  This includes designing and building the data and computational infrastructure that powers our prime editing programs. This role spans laboratory informatics, NGS pipeline development, and AI-enabled tooling, giving the right candidate a direct line from the work they do to the therapies we develop. You will partner closely with research scientists, computational biologists and technical development professionals, turning raw data into reliable scientific insights, and building automation and AI capabilities that let teams work faster and smarter.

Our ideal candidate brings strong software engineering fundamentals, hands-on NGS pipeline experience, a practical understanding of modern AI frameworks, and the biological intuition to translate scientific needs into working systems. Equally welcome are candidates who entered this space from the life sciences side and have built serious software skills along the way.

This is an action packed and dynamic role where the successful candidate will be involved in multiple programs and activities, so excellent organizational abilities, communications and strong collaboration are critical. The ideal candidate thrives when working in a fast-paced environment, working with purpose, and making an impact for patients.

Key ResponsibilitiesNGS Pipelines and Data Infrastructure
  • Design, develop, and maintain scalable bioinformatics pipelines for NGS data analysis, including amplicon sequencing for on-target editing quantification, using Nextflow and Docker to ensure reproducibility.
  • Build and maintain data infrastructure connecting NGS instruments, electronic laboratory notebooks (e.g., Benchling), data repositories, and AWS cloud compute, including automated data ingestion, scalable storage, and provenance tracking.
  • Build APIs, MCPs, dashboards, and other internal tools that expose genomic data and analytical capabilities to scientific and cross-functional teams.
Laboratory Informatics
  • Support implementation and ongoing development of laboratory informatics systems, including data ingestion from key instruments and integration with laboratory data platforms such as Benchling.
  • Support vendor relationships and delivery outcomes for external collaborators, driving requirements, managing implementations, and ensuring high-quality delivery.
AI-Powered Tools and Automation
  • Build AI-powered and agentic capabilities that automate routine work, support scientific reasoning, and improve how data and knowledge flow across the organization.
  • Develop reusable platform components for retrieval, orchestration, and model interaction, with human-in-the-loop workflows that make AI systems transparent and practical for scientific users.
  • Identify and address automation opportunities and scalability bottlenecks across research and operational workflows.
Engineering Practices
  • Write production-grade code using Git-based workflows, peer review, testing, CI/CD, and documentation best practices; convert research prototypes into robust, maintainable software.
  • Build integrations between internal tooling and third-party platforms to support evolving scientific and operational needs.
  • Participate in cross-functional projects spanning lab operations, software engineering, and bioinformatics; recommend best practices, system architectures, and design patterns.
  • Perform code reviews and contribute to documentation of engineering and cross-functional practices.
QualificationsRequired
  • BS with 5+ years or MS with 3+ years of industry experience in Engineering, Bioinformatics, Data Sciences, or a related field. Candidates with biotech or life sciences with substantial software experience are strongly preferred.
  • Strong Python development; proficiency with Nextflow (or comparable workflow tools), Docker, AWS, Linux/Unix, and Git.
  • Experience developing and deploying bioinformatic data infrastructure, particularly NGS analysis pipelines.
  • Experience implementing or integrating laboratory informatics systems, preferably including Benchling.
  • Experience developing and maintaining production-grade APIs and SDKs, and rolling out software tooling across an organization.
  • Familiarity with LLM frameworks and practical judgment about where agentic approaches add genuine value.
  • Track record of shipping software that scientific or technical users adopt and rely on.
Preferred
  • Experience building and deploying AI-powered tools or agentic systems in production or research settings.
  • Familiarity with gene editing applications (CRISPR, base editing, or prime editing), including amplicon-seq workflows and tools such as CRISPResso.
  • Familiarity with relational databases and data visualization tools (e.g., Plotly Dash, Streamlit, Spotfire).
  • Experience in a GxP or regulated software environment (21 CFR Part 11, GAMP 5).
  • Experience owning vendor relationships and delivery outcomes for external collaborators in laboratory informatics contexts.
Why This Role

Prime editing is a precise technology, and that precision depends on strong informatics, software, and scientific infrastructure. If you believe that better systems, better automation, and better access to data can translate into safer and more effective therapies, this is the right environment. You will build tools that directly shape how Prime generates, analyzes, and acts on scientific data, while helping lay the foundation for programs to come.