Director - Principal Engineer, Digital R&D DP&TS Platform and Data Engineering

Pfizer’s 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 accelerate the journey from target identification to clinical translation by leveraging advanced digital technologies, AI, and data‑driven insights.

We are building a high‑impact, outcome‑oriented platform engineering team focused on enabling scalable, secure, and resilient infrastructure and developer experiences. This role is critical to building cutting‑edge platform capabilities that power scalable, secure, and innovative advanced analytics, machine learning, and data science across the R&D organization.

This role is not narrowly defined. We are seeking self‑starters who take initiative, adapt quickly, and possess a diverse skill set. You will be expected to learn rapidly, collaborate effectively, and deliver impactful outcomes.

Reporting to the Senior Director of DP&TS Platform and Data Engineering, this role will define and deliver the platform design and architecture strategy that supports solution delivery, ensuring alignment with scientific goals, regulatory requirements, and enterprise digital strategy. You will lead a team of platform engineers and collaborate closely with product, data science, and digital partners to deliver secure, scalable, and high‑performance capabilities.

You will have direct reports with accountability for setting direction, deploying resources, and leading pay, performance, goal setting, and development discussions.

In this role, you will drive architectural decision, champion engineering excellence, and steer cross‑functional collaboration to deliver resilient, high‑impact solutions. This global role empowers you to shape infrastructure strategies, mentor technical talent, and influence product direction across regions and business units. You will also be a catalyst for Dev Sec Ops  adoption, embedding security and automation seamlessly into the development lifecycle to ensure trusted delivery at scale.

• Architect scalable, secure data platforms for scientific discovery: design and develop infrastructure that enables seamless ingestion, processing, and analysis of high‑dimensional biomedical, omics, and clinical datasets; ensuring reproducibility, compliance, and performance.
• Champion Dev Sec Ops  across research and analytical workflows: embed security and automation into development pipelines, ML model development, and platform operations to ensure privacy, compliance, security, and traceability.
• Foster collaboration across scientific and engineering teams: bridge domain and technical expertise to align platform capabilities with research goals, cultivating shared understanding and agility across integrative biology, computational research, and engineering teams.
• Influence technical direction and cross‑functional alignment: shape engineering roadmaps and advocate for cohesive platform strategies that balance innovation, risk management, and business priorities.
• Govern platform standards and lifecycle accountability: establish and uphold platform design standards, lifecycle policies, and governance models that maintain flexibility and scalability without compromising control or integrity.
• Uphold system reliability and analytical accuracy: oversee platform health through robust observability, automated testing frameworks, incident response strategies, lifecycle governance, service level agreements, and audit trails that meet regulatory, compliance, and industry principles (GxP, FAIR, etc.).
• Advance responsible innovation and domain‑specific AI adoption: identify emerging technologies and champion thoughtful experimentation with AI/ML techniques while ensuring transparency, interpretability, and ethical data use in R&D contexts.
• Lead and mentor talent in platform engineering: guide engineers and scientists in best practices, critical thinking, and cross‑disciplinary collaboration to build future‑ready data and analytical platforms; foster a culture of continuous learning, elevating technical excellence, and shaping leadership…