Solution Architect (projekt VIDRU)

Solution Architect – Scientific Data Platform

About the project

We are delivering a multi-year programme to transform fragmented legacy discovery data into a harmonised, AI-ready and FAIR-enabled data foundation supporting seven scientific data workflows across vaccines and infectious disease research.

The programme is delivered through multiple parallel value streams supported by a shared technical capability stream. We are looking for a Senior Solution Architect to own the end-to-end architecture across these workflows and help shape how scientific data is captured, integrated, governed and made available for downstream analytics and AI.

The role

As a Solution Architect, you will define the target-state architecture, integration patterns and data standards across the programme. You will work directly with scientists, business SMEs and technology teams to translate real-world research workflows into scalable technical solutions.

This is a hands-on architecture role. You will not be limited to producing governance documentation — you will design solutions, review implementation quality and drive architectural decisions throughout delivery.

What makes this role interesting

• Opportunity to shape the architecture of a major scientific data transformation programme from the ground up.
• Direct impact on how discovery data is made available for AI, analytics and future research.
• Exposure to cutting-edge Azure, Databricks, data mesh, FAIR and AI/ML capabilities.
• Close collaboration with scientists and technology teams across a highly specialised R&D environment.
• A genuine architecture + delivery role rather than a governance-only position.

What we're looking for

• Proven experience as a Solution Architect delivering technology solutions in pharma, biotech or life sciences R&D environments.
• Strong understanding of scientific/discovery data workflows and the ability to engage directly with scientists and research teams.
• Proven experience designing data mesh and/or data product architectures.
• Deep, hands-on experience with Microsoft Azure and Databricks, including lakehouse and Delta architectures.
• Experience integrating ELN, LIMS, laboratory systems, sample management/inventory solutions and scientific instruments.
• Strong knowledge of metadata management, semantic modelling, data lineage and data standards.
• Practical experience applying FAIR principles and data governance.
• Experience working with structured and unstructured scientific data, including large-volume instrument data.
• Understanding of AI/ML data enablement and what makes data suitable for machine learning and downstream AI applications.
• Experience working in regulated life sciences environments and understanding the distinction between GxP and non-GxP research.
• Strong stakeholder management skills and the ability to influence across a matrix without direct authority.
• Ability to move between scientific, business and technical discussions and turn complex requirements into practical architecture.
• Strong English communication skills.