Solution Engineer, Pipelines and Analysis (Director)

Discovery, Preclinical, and Translational Solutions (DP&TS) sits at the center of Pfizer’s scientific software work, building the digital tools that help researchers move from target identification through clinical translation. We’re looking for a senior Solution Engineer to own end-to-end platform strategy for computational pipelines and interactive analysis across DP&TS. This is a leadership role: you set the multi-year direction and standards these platforms run on, and you build and lead a team to design, build, and operate them, rather than building them yourself. You hold final decision-making authority for the roadmap, and you’re accountable for how pipeline and analysis capabilities perform not just for integrative biology, but for every research domain across DP&TS that depends on them. You’ll need deep technical grounding in pipeline orchestration, interactive analysis platforms, and cloud-native engineering, plus the people leadership experience to run an engineering team and manage contractor and vendor relationships at scale. You’ll own budget and investment decisions for the platform, own risk management across every solution in your remit, and partner across scientific, product, and engineering leadership to keep pipeline and analysis infrastructure secure and scalable as new research domains come online. You’ll own the technical strategy and direction for pipeline and interactive analysis platforms across DP&TS, not just within a single research domain. Note: this role builds and operates the infrastructure that runs pipelines; it doesn’t develop the scientific pipelines themselves. But you’ll need a solid understanding of how data scientists across multiple domains work, including HPC and GPU batch analysis, to build infrastructure that fits their needs at scale. Your decisions on platform strategy and investment affect the speed, quality, reproducibility, scalability, and compliance of research computing across all of DP&TS, and you’ll represent pipeline and analysis platforms in broader R&D digital strategy conversations that extend beyond integrative biology. The work spans scientific workflows, data engineering, and cloud infrastructure across multiple research domains, so the scope is genuinely enterprise-level. Key Responsibilities Own End-to-End Platform Strategy: hold end-to-end ownership of pipeline and interactive analysis platform strategy across DP&TS, including the roadmap, architecture, and standards that govern how these platforms serve integrative biology and other research domains that depend on them. Set Final Roadmap Direction Across Capability Leads: work with R&D capability leads across DP&TS to identify priorities, resolve competing demands across research domains, and hold final decision-making authority over the roadmap for pipeline and analysis platforms. Set Architecture and Technical Direction for Pipeline Infrastructure: set the architecture and technical direction for pipeline infrastructure (e.g., Nextflow) that handles HPC workloads across multiple research domains, including CPU- and GPU-intensive batch analysis, and hold your team accountable for building to that direction. Deliver Interactive Analysis Solutions: lead the team that builds and maintains interactive analysis environments, letting data scientists explore large-scale biological datasets securely and reproducibly. Lead the Team and Own Budget for Delivery Across Workstreams: manage a team of engineers plus contractor and vendor resources across multiple concurrent workstreams, setting technical direction, reviewing work, holding delivery to quality and security standards, and owning the budget for platform tooling, cloud infrastructure, and contractor/vendor spend. Define Standards, Governance, and Risk Management: set and maintain technical standards, governance frameworks, and risk management practices for pipeline and analysis platforms, keeping quality and consistency across DP&TS as new research domains onboard. Represent Platform Strategy in R&D Digital Strategy: bring pipeline and analysis platform priorities into broader DP&TS and R&D digital strategy discussions, extending influence beyond integrative biology into other research domains that share this infrastructure. Drive Continuous Improvement and Operational Excellence: proactively identify and address reliability, performance, scalability, and security gaps that affect research productivity and reproducibility. Keep solutions moving forward as scientific and operational needs change. Understand and Translate Scientific Needs: Build enough understanding of how data scientists work — their tools, HPC requirements, batch analysis patterns — to design infrastructure that fits their workflows. You’re not writing the pipelines, but you need to understand what they need from the platform. BASIC QUALIFICATIONS Education: Bachelor’s degree in a relevant field (e.g., Computer Science, Data Science, Bioinformatics, Engineering, or related discipline) Experience: 8+ years of progressive experience in solution engineering, data engineering, software engineering, or a related technical discipline, including experience setting technical direction and platform strategy at a multi-team or enterprise scale, not just within a single capability area Proven experience owning end-to-end platform strategy and delivery across multiple teams or capability areas in a complex enterprise or scientific environment, including requirements gathering, solution design, implementation, and ongoing maintenance Experience managing a team of engineers plus contractor or matrixed delivery resources across multiple concurrent workstreams, with demonstrated budget or vendor management responsibility and strong ability to provide technical direction, manage work quality, and drive delivery outcomes Strong technical expertise in computational pipeline orchestration tools (e.g., Nextflow, Snakemake, Airflow) and/or interactive analysis platforms, with the ability to architect and build robust, scalable solutions in cloud environments Experience influencing technology strategy beyond a single team or capability area, including budget planning, vendor management, and cross-functional roadmap decisions Technical Skills Proficiency in Python and/or other modern high-level languages used in data engineering and scientific computing Experience with infrastructure-as-code tools (e.g., Terraform, Helm, CloudFormation), CI/CD pipelines (e.g., GitHub Actions), and cloud platforms (AWS, Azure, or GCP) for deploying and operating data and compute workloads Working knowledge of high-performance computing (HPC) concepts, including CPU and GPU batch analysis workloads, job schedulers, and containerization (Docker, Singularity) as applied in scientific computing 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 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 tools they depend on Conceptual understanding of computational pipeline development and bioinformatics workflows (e.g., Nextflow, Snakemake, WDL) and the data and compute patterns they generate, even without direct pipeline development experience Experience influencing R&D digital or platform strategy beyond a single research domain, including engagement with senior scientific and technology stakeholders on multi-year investment decisions Research Domain Awareness Hands-on experience with Nextflow or other scientific workflow management systems used in omics, imaging, proteomics, or other high-dimensional biological data analysis Experience with GPU computing and HPC environments for batch analysis workloads, including job orchestration, resource management, and cloud-native compute scaling 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: 9/2/2026 The annual base salary for this position ranges from $162,900.00 to $271,500.00.* In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 20.0% 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 $146,600.00 to $244,400.00. 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. Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future. 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