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Bioinformatics Data Engineer Jobs in Portland, OR

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Bioinformatics Data Engineer information

See Portland, OR salary details

$45.6K

$139K

$252.9K

How much do bioinformatics data engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for bioinformatics data engineer in Portland, OR is $138,982.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,800.00 and $166,500.00 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 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 Portland, OR? For Bioinformatics Data Engineer jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Data Engineer jobs in Portland, OR look for? The top searched job categories for Bioinformatics Data Engineer jobs in Portland, OR are:
Bioinformatics Data Engineer jobs near you

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

e184

Portland, OR • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago

Job description

About us
e184 Repro is a biotechnology research company with the mission of advancing in vitro gametogenesis to solve one of biology's most profound challenges: returning the fundamental right to procreate.
We work at the frontier of cutting-edge technology, integrating cellular reprogramming, machine learning-guided optimization, multi-omics analysis, and automated experimental workflows to enable gamete development for individuals facing reproductive challenges.
Role overview
As a Bioinformatics Scientist with a cellular reprogramming background, you will lead computational analysis of multi-modal genomics data (scRNA-seq, ATAC-seq) to identify transcription factor combinations driving desired cell state conversion. This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring deep expertise in multi-platform scRNA-seq analysis and transcriptional regulation biology. You will collaborate closely with wet lab teams to translate computational predictions into experimental designs, while also exploring hybrid approaches that integrate foundation model insights into our reprogramming pipeline.
What you'll do
  • Lead end-to-end TF discovery for cellular reprogramming - from multi-platform single-cell genomics analysis (scRNA-seq, ATAC-seq) through GRN inference, differential analysis, and trajectory mapping - to nominate the regulators that flip cell fate.
  • Crack the combinatorial code of reprogramming by ranking TF cocktails as actionable combinations and decoding pooled perturbation and CRISPRa screens at single-cell resolution.
  • Read regulatory grammar straight off the chromatin - accessibility, motifs, synergy, repression - and build the data backbone that harmonizes modalities and platforms into something we can actually model on.
  • Sit shoulder-to-shoulder with wet lab teammates, closing the loop between predictions and screens: ingest fresh NGS readouts, retrain, re-prioritize, and pick the next experiment that teaches the model the most.

Core requirements
  • PhD in Bioinformatics, Computational Biology, or related quantitative field (or MS with 5+ years relevant industry experience);
  • Demonstrated track record applying computational TF ranking and GRN inference to cellular reprogramming problems, transdifferentiation, directed differentiation, or iPSC systems;
  • Multi-platform single-cell RNA-seq expertise: hands-on analysis from at least two different platforms, including platform-specific troubleshooting and quality control;
  • Multi-modal genomics proficiency: ChIP-seq, CUT&RUN, or ATAC-seq analysis including peak calling, differential accessibility, and TF motif enrichment;
  • Hands-on experience with established GRN inference methods to nominate or rank regulators of cell state, beyond literature-curated lists;
  • Experience analyzing pooled perturbation screens (CRISPRa, CRISPR knockout, or barcoded TF overexpression) with single-cell or bulk readouts;
  • Working knowledge of trajectory inference and pseudotime methods for mapping cell state transitions;
  • Strong programming skills in Python and R, with proficiency in Scanpy/Seurat and statistical analysis for high-dimensional data;
  • Comfortable working in a modern computational environment: cloud platforms, workflow managers, containerization, and collaborative version control;
  • Strong publication record and demonstrated cross-functional collaboration with experimental biologists.

You'll stand out with
  • Direct experience nominating or validating TF cocktails that successfully induced a cell state conversion (published or in preparation).
  • Experience with dynamical systems modeling for cell state transitions, or inverse problem approaches for TF combination ranking.
  • Background in advanced trajectory inference (optimal transport, GRN dynamics over pseudotime), Bayesian genomics, multi-omics integration, or cross-species comparative regulatory genomics.
  • Familiarity with transformer architectures in genomics and interest in hybrid classical/ML approaches to gene regulation.

Why e184?
  • Unrivaled impact: Your work directly enables technology that transforms human fertility and reproductive medicine.
  • Full-spectrum growth: Gain exposure to the entire lifecycle of discovery. From screening to mechanistic validation.
  • Best of both worlds: Experience the creative chaos of an early-stage startup with the stability of a well-capitalized company.
  • Elite collaboration: Work alongside a world-class team who are as driven as you are.

What we offer
  • Competitive salary + equity participation is considered
  • State-of-the-art facility in Portland metro area
  • Comprehensive Medical, Dental, Vision, and 401(k) with company match
  • 20 days PTO + 11 paid holidays

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.

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