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Bioinformatics Data Engineer Jobs in Utah (NOW HIRING)

Utah State University

Postdoctoral Fellow I

Logan, UT · On-site

$42K - $57K/yr

Develop systems bioinformatics approaches including Machine Learning-based to decipher host ... Focus on system and data integration, algorithm development and computational modeling of the ...

Utah State University

Postdoctoral Fellow I

Logan, UT

$42K - $57K/yr

Develop systems bioinformatics approaches including Machine Learning-based to decipher host ... Focus on system and data integration, algorithm development and computational modeling of the ...

University of Utah

Post Doc Res Assoc

Salt Lake City, UT · On-site

$65K - $73K/yr

... programmable therapeutic modules and want to work at the intersection of mitochondrial biology ... Computational and AI approaches: microprotein bioinformatics, multi-omic integration, protein ...

Danaher

Scientist, Chemistry and Raw Materials

Logan, UT · On-site

$70K - $80K/yr

... engineering, R&D, sourcing, planning, and product management. We also regularly present at ... Experience analyzing large data sets using coding (Python, R, etc.) and bioinformatic tools

All JobsBioinformatics Data Engineer JobsBioinformatics Data Engineer Jobs in Utah

Bioinformatics Data Engineer information

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 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.
What are popular job titles related to Bioinformatics Data Engineer jobs in Utah? For Bioinformatics Data Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Data Engineer jobs in Utah look for? The top searched job categories for Bioinformatics Data Engineer jobs in Utah are:
What cities in Utah are hiring for Bioinformatics Data Engineer jobs? Cities in Utah with the most Bioinformatics Data Engineer job openings:
Bioinformatics Data Engineer jobs near you
Bioinformatics Analyst - UT

Bioinformatics Analyst - UT

GATC Health

Salt Lake City, UT

Full-time

Posted 21 days ago

Job description

Company Overview: GATC Health is an innovative TechBio company at the forefront of revolutionizing pharmaceutical discovery and accelerating their development through the integration of artificial intelligence (AI), science and finance. Our company is dedicated to advancing therapeutic discoveries and improving human health by leveraging the power of technology and interdisciplinary collaboration.
 
Position Overview: We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines for primary, secondary, and tertiary analysis of data generated from transcriptional, proteomic, and mult-omic assays. As a Bioinformatics Scientist, you will innovate, develop and implement novel analysis methods for different data types from sparse to large and complex datasets to support the internal development and validation of new pharmaceutical assets and the development of end-user, customer-facing data analysis and visualization for biotech customers and stakeholders. A highly motivated scientist with broad expertise and experience in bioinformatics, computational biology, transcriptomics, proteomics and multi-omics would be an ideal fit for this position.
 
Roles and Responsibilities
  • Prep and Process data through GATC platform based on customer or internal end user requirements.
  • Implement primary and secondary analysis tools for GATC’s assays.
  • Work with cross-disciplinary R&D teams to develop and implement new discovery and risk assessment product applications.
  • Aid in Development and implementation processes and algorithms for multi-modal datasets, scalable to very large numbers of samples.
  • Engage with external collaborators on the evaluation of beta version products and analysis of novel data.
Role Requirements
  • Degree in computational biology, bioinformatics, computer science or similar.
  • Experience analyzing complex multi-omic datasets, including human or single cell data.
  • Experience implementing, and evaluating novel bioinformatics algorithms and pipelines.
  • Experience in programming in scripting (Python or similar) and interpreted languages (R, etc).
  • Demonstrated ability to become proficient in new fields and work with interdisciplinary teams.
  • Excellent verbal/written communication and interpersonal skills with scientist and non-scientists.
Role Preferences
  • Experience using or interfacing with machine learning algorithms.
  • Experience analyzing and interpreting large-scale human or single cell datasets.
  • Experience with professional software development methods and tools in a team environment.
  • Experience in programming in scripting (Python), interpreted (R ) and compiled languages (C++ / Rust / Java).
  • Experience working with collaborators, including lab scientists on multi-omic method development.
  • Experience visualizing scientific datasets and results.
  • Experience using cloud computing environments.
  • Computational biology and bioinformatics innovation.
Why Join Us:
• Opportunity to work at the intersection of technology and science, driving innovation in pharmaceutical discovery.
• Collaborative and inclusive work culture that values diversity, creativity, and continuous learning.
• Competitive compensation package, including salary, benefits, and opportunities for professional development.
• Chance to make a meaningful impact on human health and contribute to groundbreaking research and development projects.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.