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Role Summary
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 Solution Engineer to own data storage and registration for integrative biology research. This is a hands-on role: you’ll design, build, and maintain the capabilities that determine how biological research data gets stored, registered, and accessed. You’ll partner with the aligned capability lead to scope and prioritize what gets built, and work across scientific, product, and engineering stakeholders to deliver solutions that are secure, scalable, and useful for researchers.
You’ll work hands-on in AWS and GCP, building storage and data services that span both clouds and hold large omics datasets (genomics, transcriptomics, proteomics, imaging). You’ll need depth in large-scale data management and cross-cloud integration, plus enough scientific fluency to earn credibility with computational biologists and engineers alike.
Reporting to the Principal Engineer, Integrative Biology Solutions, you’ll define the technical direction for data storage and registration within the Integrative Biology space, aligning with scientific strategy, regulatory requirements, and enterprise architecture. You’re expected to be hands-on writing and reviewing real code, not just directing while also setting the standards and patterns that guide contractors and cross-functional teams. You’ll lead contractor teams as needed to extend capacity.
You’re the primary technical owner: individual engineering depth combined with cross-functional leadership. The problems are real, large-scale, heterogeneous scientific data with strict regulatory requirements, and the solutions need to hold up at research scale.
Key Responsibilities
* Own and Lead Data Storage and Registration Solutions: own data storage and registration end-to-end: design, implementation, and maintenance. Work with the Capability Lead to prioritize and scope features. Lead contractors as needed to extend capacity.
* Oversee Data Storage, Registration, and Scientific Data Stewardship: design and implement scalable data storage, experiment registration, metadata, provenance, lineage, access control, and findability capabilities. Set the storage, metadata, and stewardship standards that make Integrative Biology omics data trustworthy, reusable, and AI-ready across AWS and GCP.
* Define Standards and Best Practices: establish and maintain standards, architectural patterns, and governance frameworks for the capability area. Get them documented and adopted by delivery teams and contractors.
* Collaborate with Capability Lead and Business Stakeholders: work closely with the R&D capability lead to understand business needs, translate scientific requirements into technical solutions, and keep the backlog prioritized. Be the technical partner scientists and product stakeholders can rely on.
* Lead Contractor Teams and Drive Delivery: direct contractors as needed: provide technical guidance, review their work, and hold the line on quality, scope, and timelines.
* Provide Technical Guidance and Architecture Leadership: make and document key technical decisions, review designs and implementations, and guide technical direction for contractors and cross-functional partners in the capability area.
* Drive Innovation, Continuous Improvement, and Operational Excellence: identify and address technical debt, performance issues, and security gaps. Keep the platform moving forward in line with changing research and business needs.
* Solve Highly Complex and Cross-Disciplinary Problems: solve complex data engineering and storage challenges: large-scale heterogeneous scientific data, demanding research workflows, and the compliance requirements that come with a regulated environment.
* Build and Operate Cross-Cloud Storage and Data Services: design and implement storage, registration, and data access capabilities across AWS and GCP. Own identity federation, network connectivity, data movement, and replication between clouds so researchers can work with data where it lives without duplicating it.
* Manage Data Lifecycle, Performance, and Cost at Scale: define storage tiering, retention, archival, and egress policies for very large omics datasets. Monitor storage and transfer costs and tune for throughput on high-volume analytical and pipeline workloads.
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 software engineering, data engineering, or solution engineering roles, with demonstrated hands-on delivery of complex data storage, registration, or related platform capabilities.
* Proven experience designing, building, and maintaining data storage and registration solutions in a scientific or regulated enterprise environment, including hands-on implementation accountability.
* Experience defining standards, best practices, and technical patterns within a capability or domain area, and driving their adoption across delivery teams.
* Strong technical background in data engineering, cloud-native platforms, and software development, with the ability to contribute individually and lead contractor teams toward delivery outcomes.
* Hands-on experience designing and operating storage and data services in both AWS and GCP, including at least one production system that integrates data or services across the two clouds.
* Experience managing very large scientific or research datasets (hundreds of terabytes to petabytes), including tiering, lifecycle management, performance tuning, and cost control.
Technical Skills
* Proficiency in Python, Typescript, Java, or other modern high-level language
* Expertise in infrastructure-as-code tools (e.g., Terraform, Ansible, CloudFormation, Helm) and CI/CD (e.g., GitHub Actions)
* AWS: S3 (including storage classes and Glacier), IAM, Lake Formation, Glue, Athena, and high-throughput file storage such as FSx for Lustre.
* GCP: Cloud Storage, BigQuery, Dataproc or Dataflow, IAM and Workload Identity Federation, and VPC Service Controls.
* Cross-cloud integration: identity federation between AWS and GCP, private connectivity (Direct Connect, Cloud Interconnect, Cross-Cloud Interconnect), data transfer and replication tooling (e.g., Storage Transfer Service, DataSync), and egress cost management.
* Modern data architectures: lakehouse patterns and open table formats (Apache Iceberg, Delta Lake) that work across cloud engines.
* Omics data: working knowledge of common formats (FASTQ, BAM/CRAM, VCF, Parquet, HDF5/AnnData, Zarr) and how their size and access patterns affect storage design.
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 supporting pharmaceutical R&D, life sciences, or computational biology
* Familiarity with GA4GH standards for omics data (DRS, htsget, refget, Passports) and FAIR data principles
* Experience with scientific workflow platforms such as Nextflow, Snakemake, AWS HealthOmics, or Google Cloud Batch.
* AWS or GCP professional-level certifications, such as Solutions Architect Professional or Professional Cloud Architect.
Technical Leadership
* Recognized internal or external technical thought leade