Serve as solution architect and design authority for the team, defining reference architectures, technical standards, and reusable patterns across data, AI, and BI solutions, and providing technical sign-off on solution designs.
Lead the development of agentic AI solutions using Snowflake Cortex Agents, orchestrating across structured and unstructured commercial data to deliver conversational, self-service insight and automated workflows, with appropriate guardrails, access controls, and responsible AI practices.
Establish and own MLOps / LLMOps practices, including model and agent versioning, CI/CD for AI, automated testing and evaluation, performance and cost monitoring, and lifecycle management to ensure solutions are reliable, compliant, and production-grade.
Design and deliver strategic analytics solutions end to end, sourcing and curating data from diverse commercial data sources and applying established data engineering practices alongside emerging AI techniques.
Own the evolution of the team's data foundation, from data curation, database modeling, and ETL pipeline development toward governed, observable, AI-ready data layers, driving data quality and permanent resolution of issues at the source.
Deliver intuitive, AI-enabled decision-support and reporting tools that turn complex data into clear, actionable insight for commercial stakeholders, from country teams to global leadership.
Guide the team's transition from traditional BI and data engineering skillsets toward AI engineering, agentic AI, and modern data engineering, including infrastructure standardization, automation, and CI/CD, supported by talent pipelines, training, and mentorship.
Partner with Business Transformation & Technology, Data Science, and Insights & Strategy teams to align on foundational data assets, engineering and AI best practices, platform choices, and shared roadmaps supporting Commercial's AI and analytics agenda.
Represent the team to GCA and ICD leadership, providing visibility into delivery, capability growth, and risk, and translating technical outcomes into clear business narratives.
Contribute to documentation, playbooks, and knowledge-sharing practices, serving as a subject matter expert who raises AI and analytics capability across the organization.
Drive a positive, inclusive, and high-engagement culture focused on retention, innovation, team development, and knowledge sharing.
BASIC QUALIFICATIONS
15-20 years of relevant experience in data analytics, data science, or business intelligence, and 8+ years’ people-management experience with demonstrated success leading managers.
Proven track record of leading the design, development, and delivery of AI-enabled analytics and data engineering solutions that drive measurable business impact at scale.
Education
Advanced degree in Computer Science, Data Engineering, Management, Applied Econometrics, Actuarial Science, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field.
PREFERRED QUALIFICATIONS
Demonstrated breadth of technical leadership experience, including engineering delivery, data architecture, ETL pipeline development (e.g., dbt, Airflow), database modeling, and BI/visualization tooling (e.g., Tableau, Power BI), together with fluency in data quality/observability monitoring (e.g., Grafana), agentic AI, and modern cloud data platforms (e.g., Snowflake)
Strong ability to influence stakeholders to develop high‑performing teams by coaching direct-report workstream leads to deliver meaningful outcomes and sustained business impact.
Hands-on experience architecting and delivering AI / agentic solutions on Snowflake Cortex (Cortex Agents, Cortex Analyst, Cortex Search) or similar platforms.
Experience establishing MLOps / LLMOps practices, including model and agent deployment, evaluation, monitoring, and governance.
Proven experience as a solution architect for enterprise-scale data and AI platforms.
Work Location Assignment: Hybrid
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.
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