Senior director data and engineering
Role Summary
Pfizer’s commitment to creating breakthroughs that change patients’ lives is deeply embedded in our culture as a science-driven and patient-focused company. Central to this commitment is our use of digital technologies, AI, data, and analytics, which drive innovation across our organization. In this pivotal leadership role, the Senior Director, Data Engineering will define and execute the vision and strategy for Pfizer’s Data Platform and Data Engineering portfolio. This leader will be responsible for building and scaling robust, high-performance data platforms and pipelines that power advanced analytics, machine learning, and AI capabilities across the Commercial, R&D, and PGS (Supply Chain) organizations. Their work will be instrumental in enabling real-time insights, accelerating data-driven decision-making, and driving innovation across these critical domains. The Senior Director will lead a multidisciplinary team of data engineers, architects, and platform specialists, fostering a culture of technical excellence, continuous improvement, and customer-centricity. They will champion modern engineering practices, including CI/CD, data observability, and governance, while ensuring the seamless integration of structured and unstructured data sources. A key focus will be on scaling Data Ops infrastructure to support experimentation, pipeline deployment, and monitoring at enterprise scale. Collaboration will be essential to the Senior Director’s success. They will work closely with internal stakeholders such as the AI Center of Excellence, Commercial, Supply Chain (PGS), R&D vertical teams, to align on strategic priorities and optimize resource allocation. The role will also involve identifying and cultivating external partnerships to enhance Pfizer’s data engineering capabilities and accelerate innovation. Through visionary leadership and a deep understanding of data engineering, the Senior Director will empower their team to deliver scalable, secure, and reusable data products & solutions. Their efforts will directly support Pfizer’s mission to transform business operations through data and AI, advancing the company’s commitment to scientific discovery, commercial excellence, and supply chain resilience. Role Responsibilities Leadership- Provide strategic direction and oversight to the Data Platform and Engineering with approximately 20 direct reports, including managers responsible for domain aligned data engineering and data platform design, analysis, data product management, agile operations, program and domain platform portfolio management.
- Build trusted relationships and strong partnerships with other departments and teams to ensure team optimization for delivering strategic value across customer groups.
- Foster a collaborative and high-performing team environment, empowering the team to excel in their respective areas.
- Mentor and develop team members, promoting professional growth, knowledge sharing, and continuous improvement.
- Foster a culture of innovation and continuous improvement, encouraging adoption of new technologies and methodologies.
- Recognized internally and externally as technical / functional expert in relevant field and array of disciplines
- Leverages expertise across Division or Global Business Unit/Global Operating Unit
- Anticipate, oversee, or influence continuous improvement and innovation in day-to-day operations
- Manage and utilize significant resources outside of direct authority
- Develops solutions to highly complex or unique problems within a Division or Global Business Unit/Global Operating Unit
- Sponsor and Lead teams that set strategic direction for the Division or Global Business Unit/Global Operating Unit and may impact another
- Design and manage cross-team agile portfolio management to ensure responsiveness to changing customer needs and resource alignment.
- Drive cross-domain prioritization, focus, impact, measuring outcomes and continually improving performance.
- Collaborate with partner teams to accelerate delivery and drive reuse of technologies, solutions, models, and components.
- Collaborate on financial stewardship, budgeting, forecasting, and resource optimization.
- 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 Data Ops infrastructure to support data 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.
- Champion customer-centric, agile and product-focused mindset for superior customer experience and insights.
- 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.
- 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.
- Transformational leader with an entrepreneurial mindset and a track record of influencing technology strategy across complex, matrixed organizations.
- Experienced in leading multidisciplinary teams across platform and product design, data engineering, agile portfolio management, and program execution.
- 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.
- Inclusive leader who fosters collaboration, innovation, engagement, and productivity across diverse teams.
- Strong communicator with the ability to simplify complex technical concepts for varied audiences, including senior executives and non-technical stakeholders.
- Recognized for earning credibility with senior leadership and effectively influencing cross-functional decision-making.
- Demonstrated ability to attract, develop, and retain top engineering talent while mentoring future leaders.
- Skilled in introducing innovation and leading cross-functional change efforts that drive measurable business outcomes.
- Bachelor’s degree in a relevant field (e.g., Computer Science, Data Science, Bioinformatics, Engineering, or related discipline) with 12+ years of progressive leadership experience in data engineering, analytics, and/or AI/ML roles; or 10+ years of relevant experience for a master's degree in specified discipline.
- 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.
- The annual base salary for this position in Tampa, FL ranges from $197,900.00 to $329,800.00.
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