Head of Data Engineering & Factory

Job Description Summary

Job Title: Head of Data Engineering & Factory
#LI-Hybrid
Location: Basel Switzerland
Relocation Support: This role is based in Basel Switzerland. Novartis is unable to offer relocation support: please only apply if accessible.

Ready to shape how data powers scientific breakthroughs As Head of Data Engineering & Factory you will lead the vision and evolution of a cutting-edge Data Product Factorytransforming how scalable artificial intelligence-ready data products are built delivered and consumed across Biomedical Research. This is a high-impact leadership role where you will combine deep technical expertise with strategic thinking to industrialize data engineering accelerate innovation through automation and artificial intelligence and enable a truly data-centric organization. You will work at the forefront of modern engineering practices driving measurable outcomes while empowering teams to build reliable high-quality data products at scale.

Job Description

Key Responsibilities

• Define and execute the vision roadmap and operating model for the Data Product Factory
• Lead industrialization of scalable production-grade data product engineering across Biomedical Research domains
• Drive adoption of standardized engineering patterns reusable blueprints and contract-first design principles
• Ensure all data products are artificial intelligence-ready with standardized interfaces metadata and controlled access mechanisms
• Lead modernization of engineering practices using automation-first and artificial intelligence-native approaches
• Oversee end-to-end lifecycle of data products including build certification deployment and deprecation
• Establish and scale continuous integration continuous deployment and development and operations capabilities across platforms
• Embed governance security lineage and policy-as-code into engineering workflows by design
• Build and lead high-performing engineering teams driving technical excellence and organizational capability growth
• Partner with domain and platform leaders to align business priorities with engineering delivery outcomes

Essential Requirements

• Over 10 years of experience in software engineering platform architecture or enterprise data infrastructure
• Proven track record building and scaling enterprise data platforms or productized data systems
• Strong experience leading engineering teams within complex matrixed organizational environments
• Deep expertise in continuous integration continuous deployment and automated testing practices in production environments
• Demonstrated experience embedding governance access control lineage and compliance within engineering workflows
• Experience enabling artificial intelligence use cases through well-designed data products interfaces and metadata frameworks
• Strong ability to apply automation and artificial intelligence to improve engineering productivity and operational efficiency
• Excellent communication and stakeholder management skills with proven experience influencing senior leadership

Desirable Requirements

• Experience designing agent-compatible interfaces metadata frameworks and retrieval-augmented data access patterns
• Proven success mentoring multidisciplinary engineering teams across platform data quality and artificial intelligence domains

Commitment to Diversity and Inclusion

Novartis is committed to building an outstanding inclusive work environment and diverse teams representative of the patients and communities we serve.

Accessibility and Accommodation

Novartis is committed to working with and providing reasonable accommodation to all individuals. If because of a medical condition or disability you need a reasonable accommodation for any part of the recruitment process or to receive more detailed information about the essential functions of a position please email and share the nature of your request along with your contact information. Please include the job requisition number in your message.

Skills Desired

Clinical Trials Data Architecture Development Data Governance Data Integration Data Management Data Products Data Quality Data Science Data Strategy Drug Development Global Project Management Operations People Management