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Role title: Semantic Engineer

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$50**B. 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 Data Foundations team is looking for a Semantic Engineer to designs, build, and evolve applications and services that enable the creation, integration, and consumption of semantic data across the enterprise. This role focuses on connecting data from multiple sources into a unified semantic layer, enabling consistent meaning, governance, and AI ready data access.

The Semantic Engineer works closely with data, AI, and product teams to ensure that semantic models, knowledge graphs, and APIs can be easily discovered and consumed by both people and AI agents, supporting analytics, automation, and agentic AI use cases.

Essential Responsibilities of the Job:

• Build and maintain applications that support, scale, and integrate with the enterprise semantic layer

• Connect and harmonize data from across EY into semantic models, ontologies, and knowledge graphs

• Enable AI and agent frameworks to leverage semantic data for grounded, explainable, and governed outcomes

• Develop APIs and services that allow users and agents to discover, query, and consume semantic data

• Collaborate with data engineers, architects, and product teams to embed semantics into data products and platforms

Education & Experience:

• Undergraduate degree, preferably in Engineering.

• Data Expertise

• Experience working with Graph Databases / Triple stores

• Knowledge of SPARQL and SQL

• Conceptual understanding of data modelling

• Understanding of Ontologies

• AI Expertise

• Knowledge of Generative AI

• Understanding of AI development lifecycle

• Practical hands-on development of AI Agents

• Experience creating / consuming MCP services

• Application Development

• Experience with Python

• Experience building / using API’s

• Understanding of microservices

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.