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Bioinformatics Data Engineer Jobs in Houston, TX

Baylor Genetics

AD Scientific Innovation

Houston, TX · On-site

D. in Bioinformatics, Computational Biology, Genetics, Computer Science, Biomedical Engineering, or ... clinical data. • Track record of patents, publications, or successful product launches.

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All JobsBioinformatics Data Engineer JobsBioinformatics Data Engineer Jobs in Houston, TX

Bioinformatics Data Engineer information

See Houston, TX salary details

$41.1K

$125.2K

$227.8K

How much do bioinformatics data engineer jobs pay per year?

As of Aug 5, 2026, the average yearly pay for bioinformatics data engineer in Houston, TX is $125,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,700.00 and $149,900.00 per year, depending on experience, location, and employer.

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 does a bioinformatics data engineer do?

A bioinformatics data engineer designs, develops, and maintains data pipelines and infrastructure to process large biological datasets. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, accurate, and efficiently managed for research and analysis purposes.

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.

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 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.
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Bioinformatics Data Engineer jobs near you

Senior Bioinformatics Software Engineer

Morpheus Group

Houston, TX

Full-time

Posted 6 days ago

Job description

We are seeking an experienced Senior/Staff-Level Bioinformatics Software Engineer to provide technical leadership in the design, development, and enhancement of advanced bioinformatics software solutions. This role combines software engineering, computational biology, and data science expertise to support genomic data analysis, next-generation sequencing (NGS) workflows, and the development of scalable analytical platforms.
Key Responsibilities
  • Architect and develop innovative bioinformatics applications, analytical tools, and data processing solutions.
  • Lead the creation and optimization of genomic analysis pipelines focused on sequence interpretation, variant detection, and complex biological data analysis.
  • Partner with scientists, researchers, and cross-functional stakeholders to design studies, analyze results, and translate biological requirements into software solutions.
  • Drive technical strategy and contribute to architectural decisions for current and future software platforms.
  • Improve development processes through automation, best practices, and modern engineering methodologies.
  • Mentor engineering team members and serve as a technical resource across projects. Desired Qualifications
  • Strong background in bioinformatics software development with expertise in NGS data analysis and genomic workflows.
  • Experience working with common bioinformatics formats and tools, including sequencing alignment, variant analysis, and quality control frameworks.
  • Advanced programming skills in Python, R, or similar languages used in scientific computing.
  • Proficiency with Linux environments, cloud computing platforms, and workflow orchestration tools.
  • Experience with software development best practices, source control, testing methodologies, and containerized environments.
  • Excellent communication, leadership, and collaboration skills with the ability to work effectively across scientific and technical teams.

Background
  • Bachelor's degree in Computer Science, Bioinformatics, Data Science, Statistics, Mathematics, or a related field required; advanced degrees preferred.
  • Approximately 7+ years of experience in software engineering, bioinformatics, computational biology, or a related discipline, including demonstrated technical leadership.

This opportunity is ideal for a bioinformatics professional who enjoys leading complex technical initiatives, building scalable genomics solutions, and working at the intersection of software engineering and life sciences