Junior Software Developer contributing to the design and implementation of insurance software solutions with a focus on the Spring framework at Fadata.
About the role
- Staff Software Engineer optimizing computational cloud infrastructure for R&D teams at Pfizer. Leading strategy and stakeholder engagement for scientific workloads migration and resource management.
Responsibilities
- Lead solution design and migration strategy for R&D teams transitioning legacy scientific workloads to cloud based HPC platforms, ensuring alignment with performance, scalability, security, and cost objectives.
- Partner with scientific stakeholders to translate research needs into platform level infrastructure requirements, providing senior technical guidance on compute, storage, and parallelization approaches.
- Serve as the senior technical authority for complex HPC operational issues, defining troubleshooting frameworks, escalation paths, and long term remediation strategies for scheduler, dependency, and workflow failures.
- Own the strategy, quality, and governance of HPC documentation and knowledge assets, ensuring documentation remains accurate, accessible, and aligned with platform standards, onboarding needs, and evolving best practices.
- Lead platform level communications and stakeholder engagement related to HPC operations, including maintenance, capacity changes, and upgrades, ensuring transparency, predictability, and minimal disruption to scientific workloads.
- Define and oversee user enablement and training strategy for HPC platforms, ensuring researchers are equipped to use cloud resources efficiently, responsibly, and in accordance with platform best practices.
- Own the end to end lifecycle strategy for scientific software platforms, including selection, deployment models, upgrade planning, and deprecation, to ensure reliability, reproducibility, and broad usability across research domains.
- Establish containerization standards and adoption models for scientific workflows, overseeing the transition of complex applications to container based execution environments and ensuring consistency across teams and platforms.
- Set and govern application performance optimization standards across cloud instance types, guiding workload placement decisions to maximize performance, scalability, and cost efficiency.
Requirements
- B.S. with 7+ years or Ph.D. with 3+ years of experience in high performance computing, cloud computing, and life sciences.
- Deep Linux systems expertise supporting the design, standardization, automation, and reliable operation of scientific computing platforms and services.
- Excellent written and verbal communication skills with the ability to clearly communicate complex technical concepts to scientific, technical, and platform stakeholders.
- Demonstrated ability to lead resolution of complex technical issues while providing clear status updates and communication back to scientific stakeholders.
- Deep foundational technical expertise across HPC and cloud platforms, including Linux, Slurm, Kubernetes, GitOps, Google Cloud Platform, Spack, Cluster Toolkit, infrastructure-as-code-tooling, GPU architectures, and related scientific software ecosystems.
- Advanced experience with at least one of AWS and GCP, including knowledge of core compute and storage services relevant to HPC.
- Experience designing, operating, or supporting distributed computing environments, including Kubernetes-based environments such as GKE.
- Prior experience with HPC deployment utilities including Google Cluster Toolkit
Benefits
- 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
- health benefits to include medical, prescription drug, dental and vision coverage
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