Semantic Layer Activation Lead

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Role title: Semantic Layer Activation Lead

About the AI Ready Data Function:

EY aspires to become the world’s most trusted AI-powered professional services firm, delivering transformative value to clients and employees. Leveraging its extensive data across finance, legal, HR, and core business operations, EY is uniquely positioned to accelerate its data strategy and unlock new opportunities for growth and protection of its business.

To achieve this vision, all Service Lines and global regions must collaborate on strategic priorities aligned with EY’s “All In” goal: safeguarding the current US$50B revenue base while generating the next US$50B. Central to this effort is advancing data management across its lifecycle to enhance existing services and create innovative offerings.

EY’s AI Ready Data Strategy, led by Applied Innovation and the Global Data Office, is the foundation for this transformation. The Data Office drives applied innovation by redefining how data is discovered, managed, utilized, and scaled. A key enabler is the development of an enterprise data platform supported by robust governance, unlocking the full potential of EY’s data assets to fuel innovation and deliver next-level client service.

The Data Acquisition team plays a critical role within this function, enabling EY to source, manage, and optimize strategic data needed to support global service lines, regions, and client engagements.

Position Summary:

The Global Data Office Semantic Layer team is seeking a highly skilled and experienced Semantic Layer Activation Lead to drive the adoption of semantic layer capabilities across the enterprise in support of EY’s AI Ready Data Strategy. This role is pivotal in creating a comprehensive semantic layer offering for both internal EY stakeholders and our clients alike, in the process building a strong community of practice across the enterprise.

Essential Responsibilities of the Job:

• Design and implement a comprehensive semantic layer offering, that comprises all aspects of solution design and delivery including commercial and support models,
• Define standards, methods and tools as appropriate to help standardize the way we build semantic layers in EY
• Conceptualise and build AI Agents that can accelerate the creation, delivery and governance of the semantic layer.
• Integrate the Semantic Layer offering with the EY.ai Data Marketplace and EY.ai Simulation Hub capabilities, making it a core component of our AI Ready data strategy.
• Drive adoption of the semantic layer across the enterprise by tracking, managing, and fulfilling demand for semantic layer offerings across the enterprise, and measure the success of this offering through well-defined KPIs and metrics.
• Build training content for the AI Ready Data Academy and a faculty to impart training on Semantic Layer, in the process building a strong community of interest.
• Communicate fluently about the semantic layer and its benefits, effectively selling this offering to both internal and external clients.
• Collaborate with Super Region and Service Lines Data teams to evangelise the benefits of the Semantic Layer and identify pertinent use cases.
• Catalog and manage the creation, publishing and usage of business ontologies and also help connect all associated knowledge graphs across EY into an enterprise-wide knowledge graph.
• Oversee the deployment architecture for the Semantic layer that is performant and efficient and supports data virtualization, data materialization against a federated semantic layer design.
• Manage the design and delivery of the technical integrations for semantic layer, covering MCP server, enterprise data catalog, analytical tools and other applications in including other knowledge graph tools like PoolParty (Graphwise).

Education & Experience:

• Undergraduate degree, preferably in Engineering.
• Master’s in Business Administration is a plus.
• Strong modelling experience, both in the traditional RDBMS and semantic areas.
• Strong understanding of data concepts like Data Virtualisation and Virtual Graphs, Semantic Modelling, Knowledge Graph, Ontology and Data Cataloging.
• Hands on experience working on tools like Stardog, Graphwise, AtScale etc. with working knowledge of SPARQL.
• Proven experience in implementing and scaling semantic layers in large organizations.
• Demonstrable skills in enabling AI agents to consume from the Semantic Layer.
• Excellent business acumen to translate client needs into actionable solutions.
• Strong leadership and communication skills, with the ability to engage and influence stakeholders.

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