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Bioinformatics Data Engineer Jobs in Virginia (NOW HIRING)

IMAGINEEER LLC

Scientific Data Analyst

Arlington, VA · On-site

$110K - $115K/yr

Proficiency in at least two programming languages: Python, R, Perl, or equivalent * Experience with bioinformatics tools, databases, and high-throughput data analysis * Experience managing and ...

Imagineeer LLC

Scientific Data Analyst

Arlington, VA · On-site

$110K - $115K/yr

Proficiency in at least two programming languages: Python, R, Perl, or equivalent * Experience with bioinformatics tools, databases, and high-throughput data analysis * Experience managing and ...

CRDF Global

Biosecurity Expertise

Arlington, VA

... programming that aims to promote responsible science and technology development and prevent the ... Securing genomic databases, patient data, and bioinformatics pipelines from exfiltration or ...

CRDF Global

Biosecurity Expertise

Arlington, VA · On-site

... programming that aims to promote responsible science and technology development and prevent the ... Protecting sensitive genomic sequencing data and bioinformatics pipelines. * Secure collaboration ...

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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 Virginia? For Bioinformatics Data Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Data Engineer jobs in Virginia look for? The top searched job categories for Bioinformatics Data Engineer jobs in Virginia are:
What cities in Virginia are hiring for Bioinformatics Data Engineer jobs? Cities in Virginia with the most Bioinformatics Data Engineer job openings:
Bioinformatics Data Engineer jobs near you
Associate Bioinformatics Data Scientist

Associate Bioinformatics Data Scientist

Signature Science, LLC

Charlottesville, VA

$75K/yr

Full-time

Posted 25 days ago

Job description

Position Purpose:   

A bioinformatics data scientist is responsible for providing experimental design consulting and data analysis for large, high-throughput genomic experiments, with a focus on forensics and metagenomics. The bioinformatics data scientist will be responsible for designing and implementing annotated code for managing, manipulating, and analyzing large-scale genomic data, and for preparing thorough documentation and reporting.

This position is a full-time, on-site role at the Signature Science office in Charlottesville, VA.

Essential Duties and Responsibilities:

  • Develop tools for management, analysis and interpretation of high-density microarray and whole genome sequencing data.
  • Manage, manipulate, and analyze data using a combination of R, python, and UNIX tools.
  • Use established domain-specific open-source software and tools to manipulate and analyze genomic data.
  • Implement and execute data processing workflows and automated analytic pipelines.
  • ·     Apply literate‑programming methods to develop reproducible workflows that produce consistent, standardized tables and figures.
  • Conduct workflow benchmarking and documentation, identifying inconsistencies and resolving data problems.
  • Prepare SOPs, document source code/workflows, and write reports to summarize computational requirements, processing status, and customized analysis results.

Required Knowledge, Skills & Abilities:

  • Advanced proficiency working in a Unix/Linux environment.
  • Advanced proficiency with open-source software, tools, and databases for analyzing next-generation sequencing data (whole-genome sequencing, RNA-seq, epigenetics, microbiome, and metagenomics).
  • Proficiency working with and developing using Docker and/or Singularity container technology.
  • Proficiency using version Control software (e.g., Git or similar) to manage programming code.
  • Proficiency with Python, Perl, or another scripting language.
  • Proficiency with R, RMarkdown, and the "tidyverse" tools for data analysis.
  • Preferred: Experience with NextFlow, SnakeMake, or similar workflow/pipeline management systems.
  • Preferred: Familiarity with developing and querying relational databases.
  • Preferred: Familiarity with AWS and/or Azure cloud computing.

Education/Experience:

  • BA or BS in Computer Science, Bioinformatics, or related field
  • Experience managing and analyzing large-scale datasets produced sequencing platforms and delivering solutions for managing, visualizing, analyzing, and interpreting genomic data
  • Experience using Linux/Unix text processing tools, R, and other open-source tooling to manipulate and format data, to assess data quality, and analyze data.

Clearance:

  • This position requires that the candidate be willing and able to complete a successful background screening for a security clearance. Candidates with a current security clearance will receive preference.

 

Supervisory Responsibilities:

  • May serve as a bioinformatics task lead.

 

Working Conditions/ Equipment:

  • Ability to work in varying conditions to include: traditional office environments with sedentary extended periods required for code development and testing.