Director, Analytics Engineering & AI

Analytics Gateway, part of Pfizer's Global Commercial Analytics (GCA) organization, is the India-based Global Capability Center that delivers innovative, high-quality analytics solutions at scale to Pfizer's data-driven International Commercial Division (ICD).

The Director, Analytics Engineering & AI leads Analytics Gateway’s Data Engineering and Business Intelligence/Data Visualization teams which consists of ~20 colleagues who, in addition to traditional Data Engineering and Data Visualization offerings, are increasingly focused on designing, building, and scaling AI-enabled analytics solutions.

Key Responsibilities:

• Lead the ~20 colleagues that form the AI Engineering, Data Engineering, and Business Intelligence / Data Visualization teams within the Mumbai-based Analytics Gateway Global Capability Center supporting Pfizer's International Commercial Division.
• Act as the AI Engineering lead, owning the design, build, deployment, and scaling of AI-enabled and agentic solutions for commercial use cases, from proof of concept to production.
• Serve as solution architect and design authority for the team, defining reference architectures, technical standards, and reusable patterns across data, AI, and BI solutions.
• 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.
• 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.
• 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.
• Deliver intuitive, AI-enabled decision-support and reporting tools that turn complex data into clear, actionable insight for commercial stakeholders.
• Guide the team's transition from traditional BI and data engineering skillsets toward AI engineering, agentic AI, and modern data engineering.
• 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.
• Represent the team to GCA and ICD leadership, providing visibility into delivery, capability growth, and risk.
• 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.
• 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, database modeling, and BI/visualization tooling.
• Strong ability to influence stakeholders to develop high‑performing teams.
• Hands-on experience architecting and delivering AI / agentic solutions on Snowflake Cortex.
• Experience establishing MLOps / LLMOps practices.
• Proven experience as a solution architect for enterprise-scale data and AI platforms.