Pfizer
Computational Biology
DataEngineer-ComputationalBiology
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer - Computational Biology at Pfizer. Skills: Nextflow pipelines, Cloud infrastructure, Omics ecosystem platform, Data products, Python. Apply bioinformatics and cloud engineering practices to develop, operationalize and evolve production bioinformatics pipelines. Develop, deploy, and operate production‑grade Nextflow pipelines on cloud infrastructure”
What You'll Achieve.
Deliver reliable data products for Pfizer R&D research units; Advance a cutting‑edge *omics ecosystem platform for Pfizer R&D; Enable the generation of testable hypotheses across the entire drug discovery value chain; Ensure scalable and reproducible execution of Nextflow pipelines; Strengthen pipeline quality, sustainability, and adoption of best practices
Industry & Context.
Experience solving complex analyses/problems in a timely fashion
Permanent work authorization in the United States, Live within commuting distance and work on-site an average of 2.5 days per week or more as needed
What They're Looking For.
Must Have
PhD in Computational Biology, Biology, Physics, Statistics, or a related technical discipline, Masters in Computational Biology, Biology, Physics, Statistics, or a related technical discipline and a minimum of two years of experience developing data products and data integration solutions in a research or industry environment, Single‑cell/NGS, functional genomics, genetics, or proteomics data analysis experience, Hands‑on experience developing Nextflow pipelines for processing NGS data, full‑stack programming skills with a focus on Python, Experience solving complex analyses/problems in a timely fashion, Excellent communication and collaboration skills with experience working effectively in cross-functional teams
Nice to Have
Background or demonstrated interest in life sciences, pharmaceutical research, drug discovery, or bioinformatics., Proven expertise in software engineering best practices, including python package development, DevOps, cloud architectures, CI/CD, and engineering tooling, Hands-on experience handling, processing, integrating, and analyzing large heterogenous data sets data in a drug discovery research environment, Experience with Claude Code or equivalent, publication record with demonstrated contributions to the field
What You'll Do.
Apply bioinformatics and cloud engineering practices to develop
operationalize and evolve production bioinformatics pipelines
and operate production‑grade Nextflow pipelines on cloud infrastructure
Own pipeline lifecycle management
and reliability improvements for reusable workflows
Implement DevOps best practices for pipelines and platform services
Develop and evolve an omics data platform that enables efficient
scalable processing and delivery of omics datasets as reliable data products
Drive collaborations with external partners and vendors to strengthen pipeline quality
and adoption of best practices
How You'll Work.
Team & Collaboration
Partnering with wet‑lab and research scientists to translate data analysis requirements into robust, production‑ready pipeline and platform solutions; Driving collaborations with external partners and vendors; Experience working effectively in cross-functional teams
Communication Scope
Excellent communication and collaboration skills
Full Job Description
**ROLE SUMMARY** You will apply strong bioinformatics and cloud engineering practices to develop, operationalize and evolve production bioinformatics pipelines to deliver reliable data products for our Pfizer R&D research units. You will be a key contributor to a dynamic and pioneering team dedicated to advancing a cutting‑edge *omics ecosystem platform for Pfizer R&D. You will leverage your expertise to design innovative approaches that extract valuable insights from Pfizer’s proprietary and external datasets, enabling the generation of testable hypotheses across the entire drug discovery value chain. **ROLE RESPOSIBILITIES** * Developing, deploying, and operating production‑grade Nextflow pipelines on cloud infrastructure, ensuring scalable and reproducible execution. * Owning pipeline lifecycle management, including upgrades, troubleshooting, performance tuning, and reliability improvements for reusable workflows. * Implementing DevOps best practices for pipelines and platform services (e.g., CI/CD, automation, and engineering tooling). * Partnering with wet‑lab and research scientists to translate data analysis requirements into robust, production‑ready pipeline and platform solutions. * Developing and evolving an omics data platform that enables efficient, scalable processing and delivery of *omics datasets as reliable data products. * Driving collaborations with external partners and vendors to strengthen pipeline quality, sustainability, and adoption of best practices. **BASIC QUALIFICATIONS** * PhD in Computational Biology, Biology, Physics, Statistics, or a related technical discipline * Masters in Computational Biology, Biology, Physics, Statistics, or a related technical discipline and a minimum of two years of experience developing data products and data integration solutions in a research or industry environment * Single‑cell/NGS, functional genomics, genetics, or proteomics data analysis experience * Hands‑on experience developing Nextflow pipelines fo
Applying for this Data Engineer - Computational Biology role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Pfizer?
Real rants from real employees. Read before you apply.