Solution Architect projekt VIDRU

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.

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.

,[Define and maintain the end-to-end target architecture across scientific data workflows., Design data mesh and data product architectures, including ownership, data contracts, quality expectations and lifecycle management., Design cloud data solutions using Microsoft Azure and Databricks, including lakehouse/Delta architectures, data pipelines, secure networking, secrets management and observability., Define integration architectures connecting ELN, LIMS, sample inventory systems and scientific instruments with governed data platforms., Architect solutions for both structured and unstructured scientific data, including high-volume instrument outputs, provenance and schema evolution., Define metadata models, naming conventions, identifier strategies and data lineage., Operationalise FAIR data principles, supporting cataloguing, discoverability, stewardship and appropriate access models., Ensure scientific data is structured and exposed in a way that enables AI/ML use cases, including training and feature pipelines and machine-accessible interfaces., Define and promote architectural standards across the programme while maintaining appropriate flexibility for exploratory research environments., Apply appropriate data integrity and regulatory controls across GxP and non-GxP R&D environments., Work closely with scientists and research teams to understand assay and experimental workflows and translate them into technical solutions., Align scientific leads, business SMEs and multiple technology functions in a matrix environment., Review solution designs and implementation quality and provide architectural guidance throughout delivery.] Requirements: Microsoft Azure, AI, Machine learning, GXP, Stakeholder management