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Bioinformatics Data Engineer Jobs (NOW HIRING)

Data Engineer

Bethesda, MD · On-site

$122K - $146K/yr

Black Canyon Consulting LLC is seeking Data Engineers to support their work for the National Center ... bioinformatic algorithms and developing cloud-ready tools and pipelines. Responsibilities : • You ...

Data Engineer

Bethesda, MD · On-site

$122K - $146K/yr

Black Canyon Consulting LLC is seeking Data Engineers to support their work for the National Center ... bioinformatic algorithms and developing cloud-ready tools and pipelines. Responsibilities : • You ...

ROSALIND empowers Scientists globally to discover life's unknowns through genomic data interpretation. As a Bioinformatics Engineer, you will develop software for analyzing and visualizing complex ...

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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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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:

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

For Bioinformatics Data Engineer jobs, the most frequently searched job titles are:

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.

Microbiologist IV (Genomic Data Engineer)

Atlanta, GA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Job description

Great Hill Solutions, LLC is part of the Seneca Nation Group (SNG) portfolio of companies. SNG is Seneca Holdings' federal government contracting business that meets mission-critical needs of federal civilian, defense, and intelligence community customers. Our portfolio comprises multiple subsidiaries that participate in the Small Business Administration 8(a) program. To learn more about SNG, visit the website and follow us on LinkedIn.

Our team of talented individuals is what makes us successful. To support our team, we provide a balanced mix of benefits and programs.Your total rewards package includes competitive pay, benefits, and perks, flexible work-life balance, professional development opportunities, and performance and recognition programs. We offer a comprehensive benefits package that includes medical, dental, vision, life, and disability, voluntary benefit programs (critical illness, hospital, and accident), health savings and flexible spending accounts, and retirement 401K plan. One of our fundamental principles is to offer competitive health and welfare benefits to our team members, providing coverage and care for you and your family. Full-time employees working at least 30 hours a week on a regular basis are eligible to participate in our benefits and paid leave programs. We pride ourselves on our collaborative work environment and culture, which embraces our mission of providing financial and non-financial benefits back to the members of the Seneca Nation.

Great Hill is seeking a Microbiologist IV (Genomic Data Engineer) in Atlanta, GA. 

The Microbiologist IV (Genomic Data Engineer) will provide scientific support to achieve the mission of the Coronavirus and Other Respiratory Viruses Division (CORVD). The role supports pathogen genomics, public health surveillance, outbreak detection, and epidemiological investigations through advanced genomic data engineering, integration, and analytics. The role also collaborates with multidisciplinary scientific teams, maintains technical documentation, prepares reports and scientific communications, and contributes to continuous improvement of data engineering and data management practices in support of public health objectives.

Job Description 

  • Develop, maintain, and optimize distributed data pipelines using Hadoop ecosystem tools (Hadoop Distributed File System, Spark, Hive, Impala).
  • Manage large-scale ETL workflows involving genomic, epidemiological, and laboratory datasets to support bioinformatic workflows.
  • Implement and optimize data validation, transformation, harmonization, and standardization workflows to ensure consistent, high-quality outputs.
  • Ingest, harmonize, and manage genomic datasets from external repositories (e.g., NCBI GenBank, Sequence Read Archive) and maintain pipelines for routine updates and submissions.
  • Work with genomic sequence files and associated metadata and integrate them into epidemiological and laboratory surveillance systems.
  • Ensure appropriate handling of sensitive public health data and compliance with data governance expectations.
  • Maintain reproducible workflows and version-controlled pipelines (e.g., Git) and prepare associated technical documentation.
  • Collaborate with bioinformaticians, laboratory scientists, and epidemiologists to translate scientific questions into scalable engineered data workflows.
  • Support development of analytical methods for outbreak detection and situational awareness, including Spark/SQL-based analysis.
  • Document advanced data lineage, governance processes, or other high-level data management structures beyond required quality controls.
  • Prepare reports, summaries, or scientific communication materials, and contribute to publications when appropriate.
  • Be proficient in common programming or scripting languages, such as Python, Rust, Scala, and/or Bash
  • Be present on site and attend weekly team meetings and provide updates on data engineering activities, pipeline performance, and ongoing tasks.

QUALIFICATIONS

Education and Experience:

  • Bachelor's degree in Bioinformatics, Data Science, Genomics, Computational Biology or a related field.
  • Master's degree is preferred in a relevant technical or scientific discipline.

Required Skils/Qualifications:

  • Proficiency with Hadoop ecosystem technologies, including: Hadoop Distributed File System (HDFS), Apache Spark, Apache Hive, Apache Impala,
  • Strong experience in data engineering, ETL development, and large-scale data integration.
  • Experience with genomic, laboratory, epidemiological, or public health datasets.
  • Ability to develop and optimize data validation, transformation, harmonization, and standardization processes.
  • Experience ingesting and managing datasets from external genomic repositories such as NCBI GenBank and Sequence Read Archive (SRA).
  • Proficiency working with genomic sequence files and associated metadata.
  • Experience with version control systems, particularly Git.
  • Knowledge of data governance, data quality management, and secure handling of sensitive health-related information.
  • Proficiency in one or more programming and scripting languages such as: Python, Scala, Rust, Bash.
  • Strong analytical, problem-solving, and technical documentation skills.
  • Ability to collaborate effectively with multidisciplinary teams including bioinformaticians, epidemiologists, and laboratory scientists.
  • Ability to work on-site and participate in regular team meetings and project updates.

Desirable Skills/Qualifications:

  • Master's degree or higher in Bioinformatics, Computational Biology, Computer Science, Data Science, Public Health Informatics, or a related discipline.
  • Experience supporting pathogen genomics and infectious disease surveillance programs.
  • Advanced experience with Spark-based analytics and large-scale distributed computing environments.
  • Familiarity with bioinformatics workflows, genomic analysis pipelines, and sequence data management.
  • Experience with analytical methods related to outbreak detection and situational awareness.
  • Knowledge of public health surveillance systems and laboratory information management systems.
  • Experience creating and maintaining data lineage documentation and enterprise data governance frameworks.
  • Experience contributing to technical reports, scientific publications, or peer-reviewed research.
  • Familiarity with cloud-based data platforms and modern data engineering practices.
  • Strong communication skills with the ability to translate scientific and public health requirements into scalable technical solutions.