EY's Consulting Services is a dynamic unit offering integrated solutions leveraging deep industry expertise and robust functional and technical capabilities. Our Data and Analytics team tackles complex challenges to drive better business outcomes, making advanced analytics integral to client decision-making.

This Semantic Data Architect role focuses on leading the design and implementation of enterprise-scale semantic data platforms. You will architect solutions for advanced analytics, AI, Knowledge Graphs, intelligent data discovery, and governed enterprise data modeling. The position demands expertise in data modeling, semantic architecture, ontology engineering, knowledge graph design, and AI-ready information architecture, bridging business concepts with technical data assets.

Develop ontologies using RDF/OWL, taxonomies, and SKOS to standardize knowledge representation. Collaborate with stakeholders to define business concepts and translate requirements into ontology-driven models. Establish semantic governance processes, metadata standards, and manage the ontology lifecycle.

Lead conceptual, logical, and physical data modeling across enterprise domains. Create and maintain enterprise, canonical, domain, and semantic models aligning business terminology with various data structures. Translate business needs into robust information models supporting Microsoft Fabric, Power BI, Knowledge Graphs, and AI retrieval frameworks.

Design and implement enterprise Knowledge Graph solutions, building semantic layers for AI, intelligent search, and GraphRAG. Integrate diverse data types into knowledge graphs and guide graph data modeling patterns. Architect solutions using Microsoft Fabric, establishing metadata-driven patterns for data integration, governance, analytics, and AI.

Enable AI and Generative AI solutions through semantic enrichment and contextualized data models. Support GraphRAG, enterprise search, and intelligent agents, designing semantic frameworks for improved LLM grounding and knowledge retrieval. Define enterprise standards for ontology management and knowledge graph assets using platforms like Microsoft Purview and Collibra.

A minimum of 10 years of experience in Data Architecture, Data Engineering, or Enterprise Information Management. A strong foundation of 5+ years in semantic technologies, knowledge modeling, and enterprise data modeling is essential.

Proven hands-on experience with Microsoft Fabric, semantic models, Power BI semantic layer, and various data modeling techniques (conceptual, logical, physical). Expertise in RDF/OWL ontology engineering and Knowledge Graph platforms is required, alongside experience with governance platforms like Microsoft Purview or Collibra.

Experience with data modeling tools such as ER/Studio, Erwin, SAP PowerDesigner, or Hackolade is preferred. An architect's mindset is crucial, enabling you to connect business concepts with data models, semantic assets, and AI-ready knowledge structures. Strong stakeholder engagement skills are necessary to collaborate effectively across business, architecture, engineering, and governance teams.