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Accenture

Advises businesses and runs their technology

Knowledge Engineer

Data ManagementConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • At least five years of experience in knowledge engineering, ontology design, or semantic modelling, including ownership of the knowledge engineering approach on complex programmes.
  • Expertise in ontology engineering, authoring OWL ontologies, RDFS schemas, SHACL constraint shapes, and SPARQL queries, with enterprise delivery experience.
  • Hands-on experience with graph databases and knowledge graph platforms such as Neo4j, Amazon Neptune, Stardog, or GraphDB.
  • Proficiency with semantic tooling such as Protégé, TopBraid Composer, or equivalent ontology authoring environments.
  • Understanding of how semantic models connect to downstream data products, metadata catalogues, and AI/ML enrichment workflows, and ability to assure the integration.
  • Knowledge of property graph modelling and ability to move between RDF-based and property graph paradigms depending on platform and use case.
  • Experience with entity resolution, semantic search, and knowledge-driven RAG architectures.
  • Experience working within modern data architectures, including data mesh, data lakehouse, and federated governance models.
  • Background in linked data principles (W3C standards) and LLM grounding techniques, including GraphRAG and ontology-grounded generation, with practical enterprise experience.
  • Ability to engage technical teams and business subject matter experts.

Responsibilities

  • Own ontology and semantic strategy across C4AD engagements, setting the approach, standards, and quality bar for knowledge engineering across the practice.
  • Assure semantic layers that ground enterprise AI by reviewing, governing, and signing off on the ontological structures that AI systems in programmes reason over.
  • Design, develop, and govern enterprise ontologies, taxonomies, and knowledge graphs that represent business domains, their relationships, and governing rules.
  • Build and govern semantic models using RDF/OWL, SHACL, and SPARQL, and property graph approaches using platforms such as Neo4j, Amazon Neptune, or Stardog.
  • Apply and adapt industry-standard ontologies such as FIBO, BIAN, GS1, and TM Forum to organisation-specific semantic requirements.
  • Develop and enforce semantic modelling standards, naming conventions, versioning, and curation workflows, and drive their adoption across delivery teams.
  • Enable AI and ML applications through knowledge graph enrichment, entity resolution, semantic search, and ontology-powered RAG pipelines.
  • Engage business subject matter experts and domain experts to elicit and formalise implicit business rules, relationships, and concepts into explicit ontological structures.

Desired Qualifications

  • Industry experience in Financial Services, Government, Health, Energy, or Utilities sectors in APAC.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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