EY - GDS Consulting - AI And DATA - MS Security Consultant
Ernst and Young20 days ago
Hyderābād, IndiaStaff+
Responsibilities
- Develop domain ontologies using RDF, OWL, taxonomies, controlled vocabularies, and SKOS concept schemes.
- Lead conceptual, logical, physical, canonical, dimensional, domain, and semantic data modelling across enterprise domains.
- Design and implement enterprise knowledge graphs supporting AI, intelligent search, recommendations, GraphRAG, and contextual retrieval.
- Architect Microsoft Fabric solutions including Lakehouse, Data Warehouse, OneLake, Data Factory, and Semantic Models.
- Enable generative AI, retrieval-augmented generation, vector search, semantic search, intelligent agents, and enterprise knowledge retrieval through governed semantic foundations.
- Define metadata standards, ontology lifecycle processes, semantic governance frameworks, business glossaries, lineage practices, and reusable modelling patterns.
- Use platforms such as Microsoft Purview and Collibra to support metadata and governance requirements.
- Conduct architecture reviews, define enterprise standards, provide technical leadership, and mentor architects, engineers, and data stewards.
- Partner with business analysts, domain subject matter experts, data architects, data engineers, AI engineers, and governance teams.
Requirements
- 10+ years of experience in data architecture, data engineering, enterprise information management, or enterprise data modelling-led architecture roles.
- 5+ years of hands-on experience in semantic technologies, knowledge modelling, and enterprise data modelling.
- Hands-on experience with Microsoft Fabric, semantic models, the Power BI semantic layer, RDF/OWL ontology engineering, knowledge graph platforms, and governance platforms such as Microsoft Purview or Collibra.
- Experience with conceptual, logical, and physical data modelling, including normalization, denormalization, dimensional modelling, star and snowflake schemas, slowly changing dimensions, reference data, master data, metadata modelling, and model version management.
- Experience with knowledge graphs, graph data modelling, GraphRAG, semantic search, enterprise search, relationship modelling, hierarchies, and contextual knowledge retrieval.
- Preferred experience with ER/Studio, Erwin, SAP PowerDesigner, Hackolade, or equivalent data modelling tools.
- Strong ability to connect business concepts, enterprise data assets, semantic models, knowledge graphs, and AI-ready information structures.
- Strong stakeholder engagement, architecture leadership, governance, explainability, traceability, and lineage-awareness skills.
- Wealth and Asset Management experience and familiarity with Aladdin, Investrans, eFront, position data, security master, IBOR, ABOR, or benchmark performance is preferred.
Benefits
- Support, coaching, and feedback from colleagues.
- Opportunities to develop new skills and progress your career.
- Individual progression planning and practical experience alongside education and coaching.
- Freedom and flexibility to handle the role in a way that suits the employee.
- Work in an interdisciplinary environment emphasizing high quality and knowledge exchange.
- Meaningful client projects spanning start-ups to Fortune 500 companies.
Tech Stack
Neo4j
Categories
Data Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.