Director, AI Data Engineering Tech Lead

Pfizer, S.A. de C.V; Hinoba-an; Hybrid; PHP 8,135,000 - 11,890,000; Full time

Benefits offered by this job

Competitive compensation

Hybrid work arrangement

Job summary

Pfizer is seeking an AI Data Engineering and Tech Lead to design, guide, and lead a team delivering AI-enabled data products. You will shape end-to-end data product engineering from user requirements to production deployment, mentor a high-performing team in India, and ensure production-grade delivery with solid engineering practices.

You will partner with global commercial teams and stakeholders, drive rapid prototyping, and implement CI/CD, security, and observability standards to accelerate

Qualifications

• Bachelor's or Master's in CS or related field.
• 10+ years in data engineering/science or related technical fields.
• 5+ years leading technical teams with people management.
• Strong hands-on experience building AI ready data products end-to-end.
• Proficient in SQL, Python; Snowflake experience preferred.
• Experience with AWS or Azure, Docker/Kubernetes, CI/CD.
• Experience with Collibra data catalogues and data quality tools.
• Experience with observability and production-grade data platforms.
• Experience with anonymized patient data (EMR/Claims) a plus.
• Strong English communication across global time zones.

Responsibilities

• Own end-to-end engineering delivery of AI enabled data products from user stories to production.
• Partner with Product Owners and stakeholders to ensure value delivery.
• Design reusable data/model pipelines for scalable analytics ecosystems.
• Lead and mentor a high-performing data engineering team in India and beyond.
• Establish CI/CD, testing, deployment standards and security controls.

Skills

Data engineering

Data science

AI

Python

SQL

Snowflake

Cloud AWS/Azure

Docker/Kubernetes

CI/CD

Observability

DevSecOps

Leadership

Architecture design

Education

Bachelor's or Master's in CS/Data/DS

MS/PhD preferred

Tools

Snowflake

Collibra

Dataiku DSS

SageMaker

Tableau/Power BI

GitHub Actions

Docker/Kubernetes

Job description

We're in relentless pursuit of breakthroughs that change patients' lives. We innovate every day to make the world a healthier place.

Pfizer offers competitive compensation and benefits programs designed to meet the diverse needs of our colleagues.

Join Pfizer International Commercial Division, Business Transformation organization to leverage cutting-edge technology for critical business decisions and enhance customer experiences for colleagues, patients, and physicians. Our team of data engineering, data science, and AI professionals is at the forefront of Pfizer's transformation into a digitally driven organization, using data science and AI to change patients' lives, leading process and engineering innovations to advance AI and data science applications from prototypes and MVPs to full production.

As the AI Data Engineering and Tech Lead you will design, guide and lead the engineering team to provide reliable and stable AI ready data products and solutions. Your team will architect and develop shared artifacts, tooling and deployment standards that accelerate AI enabled data products.

This role is the technical anchor for a portfolio of foundational data products as priorities and defined by the business strategy, owning end-to-end data product engineering from user requirements through production deployment.

This is a product-focused technical leadership role. You will ensure that every feature shipped meets user expectations, is production-grade, and is built on solid engineering practices. You also build and mentor a high-performing data engineering team in India (Mumbai/Chennai) that delivers with speed, quality, and autonomy.

AI Data Engineering Vision

• Own the end-to-end engineering delivery of AI enabled data products in the portfolio: from user story refinement and technical design through development, testing, and production release
• Drive data product vision alignment by partnering with Product Owners and commercial stakeholders to ensure every feature delivers measurable user value
• Enable parametrized, automated, and reusable data/model pipelines that accelerate feature delivery and ensure interoperability across the analytics ecosystem
• Stay current with emerging AI data engineering technologies and evaluate their applicability to International Commercial product roadmap

Application Development & Stakeholder Collaboration

• Partner with global commercial teams, brand leads, and regional stakeholders to deeply understand user workflows, pain points, and unmet needs
• Translate user requirements into technical specifications, ensuring alignment between business intent and engineering execution
• Drive iterative development cycles with rapid prototyping, user feedback loops, and continuous improvement
• Coordinate with enterprise Data and AI Platform teams to leverage shared infrastructure while maintaining product delivery velocity

Engineering Excellence & Quality

• Establish and maintain CI/CD pipelines, automated testing, and deployment standards that ensure reliable, frequent releases
• Define quality standards including test coverage targets, release readiness criteria, and production monitoring
• Leverage observability tools to gain insights into system behavior and proactively address issues
• Champion DevSecOps practices: embed security controls and compliance checks into development workflows

People Leadership & Team Development

• Build and mentor a high-performing team of AI data engineers
• Set technical direction, career paths and coaching routines; foster a culture of ownership, learning and engineering excellence
• Coach direct reports to adopt best practices, improve technical skills and achieve professional growthLead contractor and vendor support to extend capabilities and maximize delivery efficiency
• Drive engineering maturity through design docs, architecture decision records (ADRs), code reviews, and continuous learning (labs, guilds, demos)

This role covers a broad spectrum of skills and we encourage you to apply even if you meet partially.

BASIC QUALIFICATIONS

• Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or related field
• 10+ years in data engineering, data science, or related technical fields
• 5+ years leading technical teams with people management responsibilities
• Strong hands-on experience building and shipping AI ready data products end-to-end
• Proficiency in SQL, Python with practical experience in Snowflake
• Experience with cloud platforms (AWS or Azure), containerization (Docker/Kubernetes), and CI/CD (GitHub Actions)
• Experience with AI ready data enablement frameworks and practical implementations, Semantics management and Enterprise data catalogues (Collibra)
• Experience with Enterprise data quality management and observability solutions
• Experience with complex data sources including anonymized patient data (EMR/Claims)
• Strong English communication skills (written and verbal); ability to work across global time zones

PREFERRED QUALIFICATIONS

• Advanced degree (MS/PhD) in Computer Science, Data Engineering, or Data Science
• Experience with full-stack web development (React, Vue; HTML, Tailwind CSS, Bootstrap)
• Experience with data science platforms (Dataiku DSS, SageMaker) and BI/visualization tools (Tableau, Power BI, Streamlit)
• Experience in regulated/compliance-aware environments (GxP, HIPAA, SOC2)
• Background in product management or product-led engineering teams
• Certifications: AWS/Azure Professional, Snowflake

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.