Director, AI Data Engineering Tech Lead

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 Pfizers 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.

1) 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

2) 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

3) 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

4) 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 growth

Lead 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

Bachelors or Masters 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

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 onPfizer Careers.