Director, Analytics Engineering & AI

ROLE SUMMARY

Analytics Gateway part of Pfizers Global Commercial Analytics (GCA) organization is the India-based Global Capability Center that delivers innovative high-quality analytics solutions at scale to Pfizers data-driven International Commercial Division (ICD). The Director Analytics Engineering & AI leads Analytics Gateways 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. Reporting to the Mumbai-based lead of Analytics Gateway the Director will oversee the execution and delivery of analytics solutions and will work with International Commercial Division stakeholders and Business Transformation and Chief Marketing Office teams to ensure Gateways technical capabilities continue to meet the businesss evolving needs.

• 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 Pfizers International Commercial Division. Manage 46 direct reports and oversee hiring colleague development and resource allocation across the team.

• 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 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 teams 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 teams 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 Commercials 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 highperforming 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.

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 .

Required Experience:

Director