Pfizer is looking to define and execute the vision and strategy for its AI, Data & Analytics (AIDA) Data Engineering and Data Excellence portfolio. This involves building and scaling robust data platforms and pipelines to power advanced analytics, machine learning, and AI capabilities across Commercial, R&D, and Supply Chain organizations, enabling real-time insights and accelerating data-driven decision-making.
Requirements
- Proven experience designing, implementing, and delivering data products to support large-scale AI and ML systems, with a strong foundation in data engineering and platform scalability.
- Deep expertise in modern data architecture, data as a product methodology & strategy, including Lakehouse design, real-time streaming, and event-driven frameworks.
- Demonstrated success in building data products and scaling ML Ops infrastructure to support enterprise-grade model experimentation, deployment, and monitoring.
- Skilled in driving engineering data products, best practices, including CI/CD for data workflows, infrastructure-as-code, data excellence, and data governance.
- Experience in leading multidisciplinary teams across platform and product design, data engineering, agile portfolio management, and program execution.
- Ability to simplify complex technical concepts for varied audiences, including senior executives and non-technical stakeholders.
- Skilled in introducing innovation and leading cross-functional change efforts that drive measurable business outcomes.
Responsibilities
- Lead cross-functional teams in the design, development, and management of enterprise-scale AI, data, and analytics platforms across Commercial, R&D, and PGS (Supply Chain), leveraging technologies such as machine learning, NLP, and real-time data streaming.
- Architect and scale ML Ops infrastructure to support model experimentation, deployment, monitoring, and retraining with automation, reproducibility, and compliance at the core.
- Drive customer-centric platform and product delivery, enabling data-driven decision-making through secure, high-quality, and reusable data pipelines and services.
- Champion engineering best practices—including CI/CD for data workflows, infrastructure-as-code, and observability—while fostering a culture of innovation, continuous improvement, and technical excellence.
- Frame and execute projects and initiatives, from assessments through technical leadership, delivery, and deployment.
- Ensure shared understanding of program objectives, progress, and outcomes through stakeholder management.
- Establish partnerships across the organization to ensure program goal alignment with business strategies.
Other
- Provide strategic direction and oversight to the Data Engineering & Excellence team with approximately 20 direct reports.
- Build trusted relationships and strong partnerships with other departments and teams.
- Foster a collaborative and high-performing team environment, empowering the team to excel.
- Mentor and develop team members, promoting professional growth, knowledge sharing, and continuous improvement.
- Transformational leader with an entrepreneurial mindset and a track record of influencing technology strategy across complex, matrixed organizations.
