VP Data / Knowledge Platforms

Wood Mackenzie is the global data and analytics business for the renewables, energy, and natural resources industries. Enhanced by technology. Enriched by human intelligence. In an ever-changing world, companies and governments need reliable and actionable insight to lead the transition to a sustainable future. That’s why we cover the entire supply chain with unparalleled breadth and depth, backed by over 50 years’ experience. Our team of over 2,400 experts, operating across 30 global locations, are enabling customers’ decisions through real-time analytics, consultancy, events and thought leadership. Together, we deliver the insight they need to separate risk from opportunity and make confident decisions when it matters most.

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Wood Mackenzie Values

• Inclusive – we succeed together
• Trusting – we choose to trust each other
• Customer committed – we put customers at the heart of our decisions
• Future Focused – we accelerate change
• Curious – we turn knowledge into action

Vice President, Data and Knowledge Platforms

Reports to: Chief Product & Technology Officer

Role Overview

The Vice President of Data and Knowledge Platforms will be responsible for building and scaling the trusted, governed, ontology-driven foundation that underpins all of Wood Mackenzie’s data and knowledge assets. This leader will drive the industrialization of data pipelines, establish robust governance and quality frameworks, and package datasets into consumable APIs and data products.

This role also owns the company’s content management infrastructure — ensuring the systems that support hundreds of researchers globally are reliable, integrated, and capable of powering next-generation analytical and GenAI applications. The VP will lead the modernization of this CMS ecosystem to enable intelligent authoring, metadata automation, and seamless integration with the broader data and ontology platforms.

In addition, the VP will leverage generative AI technologies — including post-training of large language models — to transform structured data and written content into analytical insights and narrative intelligence. These capabilities will power automated synthesis, summarization, and domain-aware reasoning that enrich Wood Mackenzie’s products, knowledge base, and client workflows.

This is a cornerstone leadership role in Wood Mackenzie’s transformation into a digitally native, AI-enhanced energy intelligence platform.

Key Responsibilities

Knowledge Architecture & Ontology

• Define and maintain Wood Mackenzie’s corporate ontology and energy knowledge graph.
• Ensure all structured and unstructured datasets are mapped, linked, and discoverable within a unified knowledge ecosystem.

Data Engineering & Integration

• Industrialize ingestion from diverse internal and external sources.
• Normalize, enrich, and integrate data into consistent, high-quality pipelines.
• Partner with Product Engineering and ML teams to ensure data usability across applications and AI models.

Governance & Quality

• Establish governance, lineage, and quality frameworks across all structured and unstructured data assets.
• Implement stewardship programs with clear dataset ownership, SLAs, and automated quality monitoring.

Content Management Systems (CMS)

• Oversee the architecture, reliability, and evolution of Wood Mackenzie’s CMS, which powers research authoring and publishing globally.
• Ensure the CMS integrates with the ontology and metadata frameworks to improve content discoverability, version control, and semantic tagging.
• Drive the transformation of the CMS into an AI-assisted authoring environment, enabling metadata enrichment, automated insights, and AI co-writing support.
• Partner with Research, Product, and Engineering leaders to improve analyst productivity and content-to-product workflows.

Generative AI & Content Intelligence

• Lead initiatives that apply LLMs and GenAI to enhance content creation, summarization, and synthesis from structured and unstructured data.
• Oversee post-training and fine-tuning of domain-specific models using proprietary content and datasets.
• Develop frameworks for retrieval-augmented generation (RAG), automated insights, and dynamic content generation.
• Govern the accuracy, provenance, and compliance of AI-generated content.

Cross-Functional Collaboration

• Partner with SVPs of Architecture & Platforms, Product Engineering, and Machine Learning to ensure cohesive strategies across data, content, and AI platforms.
• Work closely with our Segments, Research leadership to align CMS, ontology, and GenAI initiatives with analyst workflows and editorial standards.
• Champion data and AI literacy across teams to drive adoption and trust.

Qualifications & Experience

• 15+ years of experience in data engineering, knowledge management, or digital content systems.
• Proven track record leading large-scale data or CMS platform transformations in knowledge-intensive organizations.
• Expertise in data governance, ontologies, knowledge graphs, and API-based data distribution.
• Experience integrating LLMs and GenAI into data or content workflows.
• Strong technical foundation in data and content architectures (e.g., Snowflake, lakehouse, headless CMS, vector databases, RAG frameworks).
• Deep understanding of metadata standards, taxonomy management, and semantic enrichment.
• Exceptional leadership and collaboration skills, capable of driving alignment across research, product, and engineering.

Key Competencies

• Visionary leadership across data, content, and AI domains.
• Ability to bridge human and machine intelligence to scale research productivity.
• Strong understanding of both technical architecture and user experience in data and content systems.
• Strategic thinker who can balance innovation with operational excellence and compliance.
• Collaborative communicator and change agent in a global matrix environment.

Success Metrics

• % of datasets and content mapped to ontology and knowledge graph.
• CMS uptime, usability, and integration KPIs.
• Improvements in data and content quality scores.
• Reduction in redundant data pipelines and manual content tasks.
• Deployment and impact of GenAI-driven authoring and analysis tools.
• Analyst and client adoption of AI-assisted knowledge workflows.

Equal Opportunities

We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability or protected veteran status. You can find out more about your rights under the law at www.eeoc.gov 

If you are applying for a role and have a physical or mental disability, we will support you with your application or through the hiring process.