Principal Engineer, Data Engineering

Pfizers mission to deliver breakthroughs that change patients lives is rooted in our commitment to science and innovation. Within Discovery Preclinical and Translational Solutions (DP&TS) we work to shorten the path from target identification to clinical translation with better software data and AI.

We are looking for a Principal Engineer Data Engineering to lead the architecture and delivery of the data engineering capabilities DP&TS depends on. The work covers lakehouse-style data platforms cloud-native ingestion and transformation pipelines data quality and observability metadata and lineage and curated domain-oriented datasets that feed analytics AI/ML and scientific computing.

This is a hands-on technical leadership role for someone who can set direction and still go deep. You will move between architecture code and operations and pick up unfamiliar problems quickly.

You will report to the Senior Director Platform and Data Engineering and work closely with the Group Product Manager Data Engineering. You will set technical direction for the data engineering roadmap work with scientific and product leaders to define data-as-a-product outcomes and guide engineers in building data systems that are reliable compliant and cost-aware. You will lead an automation-first approach (CI/CD and infrastructure-as-code) consistent patterns and the operational discipline that regulated environments and sensitive scientific data require.

The role is global. You will lead the data engineering team day to day mentor engineers set architecture and standards across teams and be measured on real improvements in time-to-data data trust and platform reliability.

Key Responsibilities

• Design and evolve the lakehouse-style data architecture that supports batch and streaming ingestion large-scale processing and secure data access for analytics and AI/ML.
• Establish reusable patterns for ingestion transformation orchestration and data modeling that speed up delivery and keep work consistent and maintainable.
• Define and run data quality observability and reliability practices for critical datasets: automated checks monitoring and alerting lineage-aware troubleshooting SLOs and SLAs and incident response.
• Work with domain teams to publish curated discoverable datasets with clear ownership documentation metadata and access controls so data gets reused rather than rebuilt.
• Build security privacy and compliance into the pipelines from the start: encryption secrets management access control auditing and retention in line with regulated environments and enterprise policy.
• Improve performance and cost across compute and storage through efficient processing sensible storage layout and lifecycle workload tuning and clear cost visibility.
• Set the bar for engineering practice: CI/CD for data infrastructure-as-code repeatable environment promotion and testing that makes delivery predictable and auditable.
• Lead and mentor the data engineering team through design reviews architecture decisions coaching and cross-team alignment building a culture of ownership and steady improvement.

BASIC QUALIFICATIONS

Education: Bachelors degree in a relevant field (e.g. Computer Science Data Engineering Software Engineering Data Science Bioinformatics or related discipline)

Experience:

• 8 years of hands-on data/software engineering experience delivering production data platforms and pipelines in cloud environments.
• Architecting and building cloud-native data platforms (e.g. AWS GCP Azure)
• Designing scalable batch and streaming data pipelines transformation frameworks and curated datasets for analytics/AI
• Implementing operational excellence: monitoring data quality automation incident response and reliability practices
• Working with regulated or sensitive datasets applying secure development practices and auditability
• 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.

Technical Skills

• Strong programming skills (Python plus one of: Java/Scala/Typescript) and strong SQL
• Experience with distributed data processing patterns and modern data architectures (e.g. lakehouse distributed compute columnar storage)
• Proficiency with CI/CD and infrastructure-as-code; ability to automate deployments and environment promotion
• Strong understanding of data governance fundamentals: cataloging lineage access control and data stewardship

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: Masters or PhD in a relevant field (e.g. Computer Science Data Engineering Software Engineering Data Science Bioinformatics or related discipline)

Domain Expertise

• Experience supporting pharmaceutical R&D life sciences or computational research; familiarity with biomedical data concepts and reproducibility expectations
• Familiarity with biomedical data standards (e.g. HL7 FHIR OMOP CDISC) and FAIR data principles

Modern Data Engineering

• Experience with lakehouse platforms and open table formats; strong understanding of scalable storage/layout strategies and workload optimization
• Experience implementing data quality observability and data reliability engineering practices in production

Technical Leadership

• Proven success in designing AI/ML platforms for scientific discovery or clinical research
• Strong record of mentoring and growing engineering talent in high-complexity domains

Strategic Capabilities

• A clear point of view on data engineering strategy and the responsible use of AI
• Experience influencing cross-functional decisions especially at the intersection of science and technology

NON-STANDARD WORK SCHEDULE TRAVEL OR ENVIRONMENT REQUIREMENTS

• Travel up to 10% may be required for business activities.
• Work Location Assignment:Hybrid

No relocation package available

Last Date to apply: July 31 2026

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.

To learn more about acceptable and prohibited uses of AI during the recruitment process please review our candidate AI-use guidelines available onPfizer Careers.