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Head of Data Engineering & Factory

Job in 4040, Basel, Kanton Basel-Landschaft, Switzerland
Listing for: Novartis
Full Time position
Listed on 2026-06-15
Job specializations:
  • Engineering
    AI Engineer (Applied/Software), Systems Engineer
  • IT/Tech
    AI Engineer (Applied/Software), Systems Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 CHF Yearly CHF 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Job Title:

Head of Data Engineering & Factory

Location:

Basel, Switzerland

Relocation Support:
This role is based in Basel, Switzerland. Novartis is unable to offer relocation support: please only apply if accessible.

About

The Role
  • 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

    Note:

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