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VP of Technology – Platform
Digital Science. Define and own engineering best practice across the Digital Science group .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in defining and delivering large-scale shared data platforms, with a strong focus on data quality, governance, and engineering best practices. Capable of leading cross-functional teams in cloud infrastructure, DevOps, and AI-enabled engineering while ensuring compliance and security.
Highest-signal resume keywords
Senior Engineering Leadership ExperienceLarge-Scale Shared Data Platform DeliveryCloud Infrastructure and DevOps ExpertiseData Quality and Governance ExperienceEngineering Operating Models and Standards Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Data Platform StrategyData Ingestion and ProcessingAPI DevelopmentData Pipeline Quality ControlInfrastructure as CodeCI/CDChange ManagementData GovernanceObservabilityLicensing Management
Soft Skills
Influencing Product LeadersCommunication with Technical and Non-Technical AudiencesTeam DevelopmentCuriosity about AIAdaptability
Tools & Technologies
DevOps ToolsCloud PlatformsMonitoring ToolsIncident Management SystemsSSO SolutionsLogging ServicesBackup and Recovery ToolsFinOps ToolsData Quality ToolsAccess Control Systems
Industry Keywords
Digital ScienceAI-Enabled EngineeringRegulated EnvironmentsM&A IntegrationPlatform ConsolidationLicensed DataCustomer-Hosted DeploymentsResearch-Intensive BusinessesData StewardshipIncremental Platform Roadmap
Tech Stack
Tools & technologiesCloudSDLC
About the role
Key responsibilities & impact- Define and own engineering best practice across the Digital Science group
- Design and lead implementation of a single Target Operating Model for engineering
- Agree and deliver an incremental platform roadmap with product leadership
- Lead platform adoption, reduce duplicated capability and retire legacy components
- Deliver a unified data platform underpinning Digital Science applications
- Consolidate ingestion implementations and establish reusable enrichment capabilities
- Deliver APIs, MCP and bulk data access with entitlements, usage tracking and access control
- Build quality, provenance, lineage, observability and change control into data pipelines
- Manage rights, licensing and stewardship for licensed, public and customer-provided data
- Support private and customer-hosted deployment models
- Maintain dependable revenue-critical data releases and legacy pipelines during transition
- Define data platform measures for freshness, processing time, quality, cost and adoption
- Set strategy and governance for shared platform services
- Build or integrate authentication, authorisation, tenancy, entitlements, SSO, logging and licensing services
- Lead architecture practice, review processes and reusable engineering patterns
- Establish standards for DevOps, infrastructure as code, deployment, release automation, monitoring, observability, incident management, security, compliance, QA, FinOps, availability, backup and recovery
- Work with the Chief AI Officer to deliver the AI plan and transition engineering to an AI-first SDLC
Requirements
What you’ll need- Senior engineering leadership experience defining and delivering platform strategy across a fragmented, acquisition-built portfolio
- Proven delivery of a large-scale shared data platform covering ingestion, processing, enrichment and delivery
- Experience with data quality, lineage and governance
- Experience building shared platform services including identity and access, authorisation, tenancy, entitlements, observability and licensing
- Experience designing and rolling out engineering operating models and standards across multiple teams, sites or businesses
- Experience leading change in long-established teams
- Experience building and developing senior teams across architecture, data, infrastructure, quality and engineering
- Strong grounding in cloud infrastructure, DevOps, infrastructure as code, CI/CD, security and resilience
- Sound build/buy/integrate judgement and pragmatic trade-off decision-making
- Ability to deliver progressively without putting current customer commitments at risk
- Ability to influence product leaders, peers and executives and communicate with technical and non-technical audiences
- Desirable: experience in data-, content- or research-intensive businesses, licensed data and rights, private or customer-hosted deployments, regulated environments, AI-enabled engineering, FinOps, cloud cost management, M&A integration and platform consolidation
- Curiosity about AI and openness to experiment and adapt
Benefits
Comp & perks- Investment in, nurturing and support of innovative businesses and technologies that make research more open, efficient and effective
- Equal opportunity employment
- Inclusive workplace culture where individuals feel valued and supported
- Diverse and collaborative working environment
- Fully remote work