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Bioinformatics Data Engineer Jobs in Auburn, AL (NOW HIRING)

All JobsBioinformatics Data Engineer JobsBioinformatics Data Engineer Jobs in Auburn, AL

Bioinformatics Data Engineer information

See Auburn, AL salary details

$35.9K

$109.5K

$199.3K

How much do bioinformatics data engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for bioinformatics data engineer in Auburn, AL is $109,523.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,200.00 and $131,200.00 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.

Bioinformatics Data Engineer jobs near you

Research Assistant Professor-Genomic Sequencing Data Analysis

Tuskegee University

Tuskegee, AL • On-site

$110 - $150/hr

Other

Re-posted 28 days ago

Job description

Research Assistant Professor-Genomic Sequencing Data Analysis

We are seeking a highly skilled and motivated Research Assistant Professor with expertise in genomic sequencing data analysis to join our multidisciplinary research team. The successful candidate will lead computational and statistical analyses of large-scale genomic datasets, including whole-genome, whole-exome, and transcriptomic sequencing, to advance projects in cancer biology, precision medicine, and related biomedical fields. This position offers the opportunity to develop independent research while contributing to collaborative team science.

  • Perform high-quality computational analysis of next-generation sequencing (NGS) data, including short and long-read whole-genome, whole-exome, RNA-Seq, and spatial transcriptomics datasets.
  • Develop and implement bioinformatics pipelines for variant calling, structural variant detection, transcriptome profiling, and integrative multi-omics analyses.
  • Apply statistical and machine learning approaches to identify genomic alterations, biomarkers, and functional networks.
  • Collaborate with wet-lab scientists to integrate genomic data with experimental results.
  • Contribute to manuscript preparation, figure generation, and presentation of findings at scientific conferences.
  • Write and contribute to competitive grant applications, providing preliminary data and computational expertise.
  • Mentor graduate students, postdoctoral fellows, and research staff in computational genomics.
  • Maintain data management, quality control, and reproducibility standards in accordance with institutional and funding agency guidelines.
Preferred Qualifications
  • Ph.D. or equivalent degree, with postdoctoral training in bioinformatics, computational biology, genomics, computer science, statistics, or related field.
  • Demonstrated expertise in NGS data analysis, including quality control, alignment, variant calling, and downstream interpretation.
  • Proficiency with bioinformatics tools (e.g., GATK, samtools, bcftools, STAR, HISAT2, Cell Ranger, Seurat) and programming languages (e.g., Python, R, Bash).
  • Experience working with high-performance computing and cloud-based analysis platforms.
  • Experience with cancer genomics, single-cell and spatial transcriptomics, or epigenomic data analysis.
Physical Demands

FLSA

FLSA Exempt

Status

Status Full-Time

Skills and Attributes
  • Familiarity with database development, workflow management systems (e.g., Nextflow, Snakernake), and reproducible research practices (e.g., Docker, Git).
  • Strong track record of peer-reviewed publications in genomic data analysis.
  • Excellent problem-solving, organizational, and communication skills.
  • Ability to work effectively in multidisciplinary research teams.
Additional Employment Details

Will this position required travel? yes

Will this position required night, weekend, and after hour work? yes

Will this positon be supported using grants or contract funding? yes

Vacancies

Number of Vacancies 1

Open Date

04/07/2026

Open Until Filled

No

Documents Needed to Apply

Required Documents

  • Resume
  • Cover Letter
  • Transcript 1
  • Letter of Recommendation 1
  • Letter of Recommendation 2
  • Letter of Recommendation 3
Optional Documents
  • Other
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