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Bioinformatics Data Engineer Jobs (NOW HIRING)

With experts in biomedical science, software engineering, and program management, we focus on ... Axle is seeking a Bioinformatics/Data Scientist to join our vibrant team at the National Institutes ...

With experts in biomedical science, software engineering, and program management, we focus on ... Axle is seeking a Bioinformatics/Data Scientist to join our vibrant team at the National Institutes ...

With experts in biomedical science, software engineering, and program management, we focus on ... Axle is seeking a Bioinformatics/Data Scientist to join our vibrant team at the National Institutes ...

## Bioinformatics Engineer IIApplylocations: Remote - Californiatime type: Full timeposted on: Posted ... Knowledge of next-generation sequencing technologies and standard bioinformatics data formats (e.g ...

What programming languages are you comfortable using for bioinformatics data analysis? * What bioinformatics areas are you familiar with? (e.g., single cell, bulk genomics, transcriptomics ...

$90K - $140K/yr

## Bioinformatics Engineer IIApplylocations: Remote - Californiatime type: Full timeposted on: Posted ... Knowledge of next-generation sequencing technologies and standard bioinformatics data formats (e.g ...

What programming languages are you comfortable using for bioinformatics data analysis? * What bioinformatics areas are you familiar with? (e.g., single cell, bulk genomics, transcriptomics ...

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Bioinformatics Data Engineer information

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$43K

$131.1K

$238.5K

How much do bioinformatics data engineer jobs pay per year?

As of Sep 14, 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 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.

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 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.

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.

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Cities with the most Bioinformatics Data Engineer job openings:

What states have the most Bioinformatics Data Engineer jobs?

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What are popular job titles related to Bioinformatics Data Engineer jobs?

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Infographic showing various Bioinformatics Data Engineer job openings in the United States as of September 2026, with employment types broken down into 67% Full Time, 11% Part Time, 11% Temporary, and 11% Contract. Highlights an 78% In-person, and 22% Remote job distribution, with an average salary of $131,053 per year, or $63 per hour.

Bioinformatics Data Engineer / Programmer

Santa Clara, CA • On-site

Full-time

Re-posted 23 days ago


Job description

Job Summary:
Omega Solutions, Inc. is seeking a Bioinformatics Data Engineer to support clinical research through data solutions. The role involves developing clinical programming code and collaborating with various teams to ensure data integrity and quality throughout the data lifecycle.
Responsibilities:
• Contribute to derived clinical feature workflows for clinical study data, working from raw data extracts, through data dissemination with a strong focus on automation and data QC.
• Assist in developing and managing interactive data visualization and analytics tools for reporting.
• Play a key role in understanding user requirements, implementing systems and authoring procedures related to system use.
• Maintain data integrity and quality throughout the data lifecycle, including ensuring clinical study-related blinding where appropriate.
Qualifications:
Required:
• BS or MS in quantitative scientific fields (computer science, engineering, mathematics, statistics, bioinformatics, etc.)
• Experience with R or Python programming
• Experience with cross-functional collaboration while ensuring data quality and commitment to analysis reproducibility
• Experience with data visualization and analytics tools
• Excellent interpersonal communication (written and verbal) and organizational skills
• Excellent team player with a demonstrated track record of success in a cross-functional team environment
• Consistent commitment to delivering on team goals with a sense of shared urgency
Preferred:
• Experience with CDISC data models is a plus
• Experience with Amazon Web Services is a plus
Company:
Omega was incorporated in 2007 in the State of California to offer high end IT Solutions ranging from IT Software and product development to technology deployment and specialize in providing software solutions to diverse business sectors in USA and World-wide. Founded in 2007, the company is headquartered in Santa Clara, USA, with a team of 11-50 employees. The company is currently Early Stage.