PGS Data Engineering Lead

Pfizer Global Supply (PGS) is transforming how data powers its end-to-end supply network. The PGS Data Engineering Lead is the division business owner accountable for PGS’s core data foundations — the architecture, design, and operations of the platforms that make supply-chain, manufacturing, quality, and master data trusted, discoverable, and usable at global scale.  

Reporting to the VP, PGS Data, Analytics & AI Transformation, the role sets multi-year strategy across structured and unstructured data in a co-owned model with Digital, who co-owns much of the underlying platform and infrastructure. The leader establishes strong security and control frameworks that protect sensitive data while enabling governed, self-service access — giving PGS a scalable, secure, cost-effective data foundation that accelerates AI, analytics, and enterprise decision-making.  

Data Scope Definition & Prioritization  

• Own the technology roadmap for both structured and unstructured data, immediately defining a clear leadership approach for unstructured data.  

• Establish and run a recurring (at least annual) process to define and prioritize the scope of data in remit and the roadmap for addressing it.  

• Continuously revisit sequencing and priorities in close partnership with Digital leadership, keeping the organization focused on the right data in the right order. 

Data Lifecycle & Access Design 

• For each dataset in scope, define how the data will be housed, secured, and made accessible for direct use by both colleagues and machines, including for training Pfizer LLMs.  

• Monitor data health and freshness with PGS Data Governance, document and surface data through the most effective channels (e.g., Collibra, Pfizer LLMs), and manage its full lifecycle from creation through retirement. 

Data Platform Strategy, Architecture & Business Ownership  

• Define and execute the division's next-generation platform strategy, owning the architecture, hosting, and operations of core data platforms (data lakes, warehouses, graph databases) across critical PGS datasets. 

• Direct Digital's solution owner on platform financials, lifecycle, and day-to-day operations, and enforce security and control frameworks that protect sensitive data while enabling governed, self-service access for AI, analytics, and emerging use cases.  

• Drive simple, robust architecture by design, setting business direction, priorities, and accountability over technical execution led by Digital and service providers (e.g., Snowflake). 

• Establish security and control frameworks that protect sensitive data while enabling governed, self-service access for colleagues and machines supporting AI, analytics, and applications.  

Data Quality Algorithms, Automation & Workflow Innovation  

• Own the system integration strategy across all in-scope platforms and tools, integrating multi-provider solutions seamlessly in the background — and make data available for training Pfizer's LLMs where appropriate, respecting all security and access requirements.  

• Design, build, and operate the algorithms and automations (including MDCAT and related workflows) that detect data outliers and route them through governance workflows for steward review and action.  

• Partner with PGS Data Governance to engineer automated data correction and redesign data models, tables, and creation processes so quality and trust are built in — then monitor performance and drive continuous improvement. 

Data Consumption & Analytic Data Products  

•  Integrate data health and freshness metrics and KPIs into Collibra, making them readily available to human users and the AI systems that rely on them for automated decision-making.  

• Partner with Enterprise Analytics to build data products on the division's core common data model, and own the consumption layer strategy that packages, structures, and delivers data for all consumers — from users querying the lakes and warehouses directly to Digital solutions powering their own applications. 

Key Capabilities

• Leading Through Change: Demonstrated experience leading leaders and teams through complex change, including navigating ambiguity, influencing across stakeholders, and sustaining performance during transformation.
• Digital Literacy and AI Fluency: Strong digital literacy, including practical experience leveraging data, digital tools, and AI‑enabled solutions to drive innovation, efficiency, and better decision‑making.
• End‑to‑End Process Thinking: Proven ability to think and operate end‑to‑end, connecting strategy to execution across functions and anticipating downstream impacts to deliver integrated, enterprise‑level solutions.

• Bachelor’s/BS in Computer Science, Data/Software Engineering, Information Systems, or related technical field with 12+ years relevant experience; OR a Master’s degree with at least 10+ years of experience; OR a PhD with 7+ years of experience 

• Demonstrated success architecting, building, and leading enterprise-scale data platforms (data lakes, warehouses, and/or graph databases) with senior-management accountability.  

• Proven leadership of a business-critical team, building a high-performing culture of trusted, independent ownership.  

• Strong pharmaceutical and supply chain business acumen, connecting business needs to the right technical tools and datasets.  

• Hands-on fluency in data modeling, schema design, and system architecture; experience building data-quality algorithms, automations, and workflow/routing platforms at enterprise scale.  

• Working knowledge of modern data platforms and tooling (e.g., Snowflake, Neo4j, Collibra, AccelData, InfoSteward) and system-integration principles across multiple providers.  

• Proven ability to partner with Data Governance and Digital, operate in a highly matrixed, federated organization, and support AI/analytics or LLM-related initiatives through platform design.  

• Fluency in English required.  

• Professional certification in a relevant cloud, data engineering, or data architecture discipline (e.g., AWS/Azure/Google data engineer credentials).  

• Strong AI, governance, and business acumen, connecting platform strategy to supply chain, manufacturing, and enterprise priorities.  

• Execution focus from strategy through operation; proven change-agent track record driving adoption at scale in large, complex organizations.  

• Excellent communication, facilitation, and influencing skills across engineers to executive leadership; strong Pfizer network across PGS, Digital, Finance, and Quality/Regulatory 

NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS  

• Up to 10% domestic and international travel.  

• Willingness to work off-hours across global time zones and extended hours during peak periods (e.g., major platform migrations or go-lives).