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.

Key responsibilities

• 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.

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.

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.