Your technical decisions affect the speed, quality, and reproducibility of research across DP&TS. The problems cross scientific workflows, data engineering, and cloud infrastructure.
Key Responsibilities
Own and Lead Solution Implementation: own visualization, analytics, and collaboration solutions for Integrative Biology end-to-end: design, build, deployment, and maintenance.
Collaborate with Capability Lead on Prioritization and Roadmap: work with the R&D Capability Lead to prioritize and scope features; translate scientific needs into concrete technical requirements and delivery plans.
Design and Implement Advanced Visualization and Analytics Solutions: architect, build, and maintain scalable visualization and analytics solutions for Integrative Biology research, including interactive dashboards, visual exploration tools, and platforms that handle large-scale biological datasets.
Build and Operate Cloud Infrastructure: design, provision, and operate infrastructure on AWS and GCP using infrastructure-as-code. Deploy and manage containerized workloads on Kubernetes (EKS, GKE), including cluster configuration, networking, access control, scaling, and cost management.
Develop Production Software: write, test, and maintain production-quality code in Python or JavaScript/TypeScript, including services, APIs, automation, and web-based visualization applications. Follow sound engineering practices: version control, code review, automated testing, and CI/CD.
Deliver Collaboration Solutions: build and maintain collaboration environments that let data scientists and research teams share and explore biological data securely and reproducibly.
Lead Contractor Teams and Delivery: direct contractor teams when needed: provide technical guidance, review work, and hold delivery to quality and security standards.
Define Standards and Best Practices: set and maintain technical standards and governance frameworks for the capability area, ensuring consistency and quality across the Integrative Biology ecosystem.
Drive Continuous Improvement and Operational Excellence: proactively identify and address reliability, performance, scalability, and security gaps through monitoring, logging, and alerting across cloud and Kubernetes environments. Keep solutions current as scientific and operational needs evolve.
Understand and Translate Scientific Needs: build a working knowledge of how data scientists use visualization, analytics, and collaboration tools — and use that understanding to build the right platform, not just a technically sound one.
Basic Qualifications
Education: Bachelor’s degree in a relevant field (e.g., Computer Science, Data Science, Bioinformatics, Engineering, or related discipline)
Experience
6+ years of progressive experience in solution engineering, software engineering, or infrastructure engineering, with hands-on design and implementation of cloud platforms and data visualization, analytics, or collaboration solutions
Proven experience owning and leading the end-to-end delivery of technical solutions in a complex enterprise or scientific environment, including requirements gathering, solution design, implementation, and ongoing maintenance
Experience leading contractor teams or matrixed delivery teams to implement technical solutions, with strong ability to provide technical direction, manage work quality, and drive delivery outcomes
Technical Skills
Proficiency in Python and/or other modern high-level languages used in data engineering and scientific computing
Hands-on experience building and operating workloads on both AWS and GCP
Production experience with Kubernetes (EKS, GKE, or similar) and containerization (Docker), including Helm or equivalent packaging
Strong software development skills in Python or JavaScript/TypeScript, with experience shipping and maintaining production code
Experience with infrastructure-as-code (Terraform preferred) and CI/CD pipelines (e.g., GitHub Actions)
Working knowledge of data engineering and data platform concepts, including data ingestion, transformation, and storage patterns relevant to supporting visualization and analytics workloads in cloud environments
Other Requirements
Demonstrated experience in working with regulated data, compliance frameworks, and secure development practices
Ability to lead complex engineering efforts across global, cross-functional teams
Fluent in English; capable of clear technical communication across scientific and engineering disciplines
Preferred Qualifications
Education: Master’s or PhD in a relevant field (e.g., Computer Science, Data Science, Bioinformatics, Engineering, or related discipline)
Domain Expertise
Experience working in pharmaceutical R&D, life sciences, academic research, or a similar scientific research environment; familiarity with how data scientists and computational biologists work and what visualization, analytics, and collaboration tools they depend on
Conceptual understanding of the data and analytical workflows used in integrative biology research, including the types of visualizations, analysis outputs, and collaborative review processes involved in omics, imaging, proteomics, or other high-dimensional biological data domains
Cloud and Platform Engineering
AWS or GCP professional certifications; CKA or CKAD
Experience with GitOps tooling (e.g., Argo CD, Flux)
Experience with observability tooling (e.g., Prometheus, Grafana, CloudWatch, Cloud Monitoring)
Experience building web front ends with modern frameworks (e.g., React) for data visualization
Research Domain Awareness
Hands-on experience with data visualization and analytics tools and platforms used in omics, imaging, proteomics, or other high-dimensional biological data analysis (e.g., Tableau, Spotfire, custom D3/Plotly/Dash applications)
Experience implementing or administering scientific collaboration solutions (e.g., electronic lab notebooks, knowledge management platforms, shared analytical workspaces) in a research or enterprise environment
Scientific Collaboration
Demonstrated ability to work collaboratively with data scientists, computational biologists, or research scientists to understand their workflows, translate their needs into technical requirements, and deliver solutions that fit their ways of working
Familiarity with FAIR data principles, scientific data management best practices, or open-source tools and ecosystems used in the life sciences research community
Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
Travel up to 10% may be required for business activities.
Work Location Assignment: Hybrid
Last Date to Apply for Job: 11/30/2026
The annual base salary for this position ranges from $124,400.00 to $207,400.00.* In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.
The annual base salary for this position in Tampa, FL ranges from $111,900.00 to $186,500.00.
This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.
Relocation assistance may be available based on business needs and/or eligibility.
Sunshine Act
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.
EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
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