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Digital Technology Lead for Information Architecture
BerkshireSource: WhatJobs
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Overview
In this role you lead information architecture and data foundation initiatives within UCB’s Patient Solutions and R&D Digital Technology team. You will design scalable data architectures, drive digital transformation, and shape the research data foundation to enable reusable and AI-ready data products. You’ll collaborate with scientists, data owners and IT partners to ensure compliant, high-quality data solutions that accelerate research, development and patient impact. This position offers global scope, cross-functional influence, and hands-on technology leadership in a hybrid work environment.
Pay / Benefits
hybrid-first work model
local hub collaboration
equal opportunity employer
inclusive culture
flexible office time (40% in office)
reasonable accommodation support
Responsibilities
Co-design the global information architecture for R&D, ensuring FAIR and ALCOA+ data governance
Lead a digital transformation portfolio to build a scalable data foundation for reusable AI-ready data products
Implement scalable metadata management to improve data quality, lineage, and discoverability
Oversee system interdependencies and scale transversal, compliant operations
Engage with scientists and data owners across global R&D and collaborate with transversal DT colleagues
Define and advance the digital technology roadmap for Patient Solutions and accelerate transformation
Key requirements
Master’s degree (minimum) in a scientific or technology field; PhD also acceptable
Deep IT expertise in designing data foundation environments with modern technologies
Hands-on experience with Databricks and Snowflake configuration/pipeline implementation and data catalogs
Experience in information architecture design for global R&D digitalization programs
Understanding of ELNs, sample registries, modeling & analytics and integrating them into a data foundation
Strong knowledge of scientific data formats, data management, metadata governance and data modeling
Experience applying AI-driven approaches to data or metadata management
Strong ability to bridge research and technology and communicate with scientific and IT stakeholders
Curious, innovative mindset with a positive can-do attitude
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