VP of Technology, Platform

• VP of Technology, Platform
• Department: Technology
• Description

About us

We are Digital Science and we are advancing the research ecosystem.

We are a pioneering technology company, and our vision is of a future where a trusted and collaborative research ecosystem drives progress for all.

We believe in better, open, collaborative and inclusive research.

In creating the next generation of tools and working in partnership with the community we tackle some of the biggest challenges to research.

In order to achieve our vision, we need innovative, inspiring and dynamic people to join our team.

Want to join us?

Your new role

DS has grown through acquisition, and its products, data and engineering practices have grown up separately.

This role leads the move from that fragmented portfolio to one platform: a single data platform and shared services that every DS product builds on, run by engineering teams working to a consistent operating model.

The VP owns engineering best practice across the group, defines and rolls out a single Target Operating Model (TOM) for engineering, and leads the transformation of today's operating model onto it.

The role also owns the foundational layers of the platform (data platform, identity and access, logging, licensing and other shared services) and is accountable for their adoption by product and engineering teams.

The core challenge is to make the whole greater than the sum of its parts.

Products should share data, services and standards, while current customer commitments and revenue-critical data releases stay dependable through the transition.

Success means a trusted, reusable and commercially valuable data foundation, less duplicated capability, and faster, more consistent delivery across DS.

The VP also works with the Chief AI Officer to deliver the AI plan, and manages the transition of DS engineering to an AI-first software development lifecycle (SDLC).

• What you’ll be doing
• Engineering strategy and operating model
• Define and own engineering best practice across the group, covering architecture, data architecture, quality, infrastructure and Fin Ops.
• Design a single, consistent Target Operating Model for all engineering, and lead the transformation of the current operating model onto it.
• Agree an incremental platform roadmap with product leadership, with visible dependencies, early wins and clear progress measures.
• Lead adoption as well as build: agree integration paths with product teams, reduce duplicated capability and retire legacy components.
• Lead the rollout of an AI-first operating model across engineering, setting standards for AI-enabled development practices.
• Unified data platform
• Deliver one data platform that underpins all DS applications and brings together data sources from across the group.
• Consolidate duplicated ingestion implementations onto a shared ingestion capability with common standards.
• Establish enrichment as a reusable platform capability, with clear ownership and a route to modernise long-standing algorithms and processes.
• Deliver the data delivery layer (APIs, MCP and bulk access) for internal products and external customers, with entitlements, usage tracking and access control built in.
• Build quality, provenance, lineage, observability and change control into data pipelines so data can be trusted and issues traced.
• Work with data owners on rights, licensing and stewardship for licensed, public and customer-provided data.
• Support private and customer-hosted deployment models as requirements are confirmed.
• Keep revenue-critical data releases and legacy pipelines dependable throughout the transition.
• Set data platform measures with product: freshness, processing time, quality, cost and adoption.
• Shared platform services
• Set the strategy for which services are centrally provided and the standards and governance for those that are not. Identity and access and data services are the first targets.
• Build or integrate shared authentication, authorisation, tenancy and entitlements, SSO, logging and licensing, and move product-specific implementations onto them.
• Agree a phased delivery plan ordered by business criticality, value, dependency and speed of adoption, with an early win in each phase.
• Decide for each service whether to refine, build or buy/adopt, and make those decisions early.
• Partner with product teams on customer-facing elements such as experience, licensing and agentic capabilities as they enter the plan.
• Architecture and engineering standards
• Lead the Group Architect and Head of Data Architecture to set a pragmatic target architecture and reusable patterns, balancing common foundations against justified product differences.
• Establish an architecture practice and review board with shared standards that support delivery.
• Set cross-cutting standards for Dev Ops, infrastructure as code, deployment pipelines and release automation, monitoring and observability, incident practice, security and compliance.
• Set quality standards through QA, and cost visibility and resilience standards (Fin Ops, availability, backup and recovery) for platform services.
• What you’ll bring to the role

Essential

• Senior engineering leader with a track record of defining and delivering platform strategy that unifies a fragmented, acquisition-built portfolio into an interoperable, service-oriented ecosystem.
• Proven delivery of a large-scale shared data platform (ingestion, processing, enrichment and delivery), including data quality, lineage and governance.
• Experience building shared platform services such as identity and access, authorisation, tenancy and entitlements, observability and licensing.
• Experience designing and rolling out an engineering operating model and standards across multiple teams, sites or businesses, and leading change in long-established teams.
• Experience leading leaders: building and developing a senior team across architecture, data, infrastructure, quality and engineering.
• Strong grounding in modern engineering practice: cloud infrastructure, Dev Ops, infrastructure as code, CI/CD, security and resilience.
• Sound build / buy / integrate judgement and the ability to make decisions early, with pragmatic trade-offs between common foundations and product needs.
• Able to deliver progressively without putting current customer commitments at risk.
• Influences and builds consensus with product leaders, peers and executives; communicates clearly with technical and non-technical audiences.

Desirable

• Experience in data-, content- or research-intensive businesses, including managing licensed data and rights.
• Experience of private or customer-hosted deployment models and regulated environments.
• Hands‑on experience of AI‑enabled engineering and of taking AI capabilities from prototype to production.
• Experience of Fin Ops and cloud cost management at scale.
• Experience of M&A integration and platform consolidation.

We're looking for people who are naturally curious about AI and comfortable exploring how it can improve the way we work — you don't need to be an AI expert, but an openness to experiment and adapt is important to us.

Don't worry if you don't meet every qualification—let us be the judge!

Studies show that many qualified candidates from under‑represented groups hesitate to apply unless they meet every single requirement.

We are dedicated to building a diverse and inclusive team and strongly encourage you to submit your application.

Living our Values

We invest in, nurture and support innovative businesses and technologies that make all parts of the research process more open, efficient and effective.

The talent we secure is fundamental to us achieving our vision and our growth plans. The values we live by are:

• We are brave in the pursuit of better
• We are collaborative and inclusive
• We are always open-minded
• We are from and for the community

At Digital Science, our vision is to see research flow seamlessly – trusted, collaborative, and accessible – fueling breakthroughs that push humanity forward.

This ambitious mission is one we achieve together, by enabling open, collaborative, inclusive research.

We firmly believe that to truly innovate and solve the complex challenges faced by our customers, from researchers and universities to funders and publishers, we need diverse perspectives, experiences, and ideas.

A rich mix of voices drives quality insights, fosters enhanced collaboration, and ultimately pushes knowledge forward more effectively.

As an equal opportunity employer, we are committed to building and nurturing a workplace where every individual feels valued and belongs.

All applicants will be considered for employment without attention to race, colour, religion, age, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

Beyond recruitment, we strive to cultivate an environment where inclusivity is woven into the fabric of our culture, enabling everyone to be their best self and do their best work.