About the Centre for Advanced Data APAC
The Centre for Advanced Data (C4AD) is Accenture's specialist centre of excellence that sets the architecture standard for modern, AI-ready data estates across APAC, and mobilises the talent to deliver them at scale.
The C4AD operates across three core disciplines: Master Data Architecture, Knowledge Engineering, and Data Products. Every practitioner in the C4AD is expected to apply agentic and generative techniques as the default way of working, not as an add-on. The centre supports large-scale data and AI transformation programmes across the region, ranging from enterprise data modernisation to AI-ready platform builds.
Job Description
Join the Centre for Advanced Data APAC as a Knowledge Engineer, where you will own ontology and semantic strategy across engagements, set the knowledge-engineering standards for the practice, and assure the semantic layers that ground enterprise AI. You will define how the C4AD approaches knowledge representation across programmes, and hold the line on quality, consistency, and semantic integrity as those programmes scale.
You will work closely with Data Architects and AI Engineers, ensuring that the ontologies and knowledge graphs you define and govern give AI systems something real, structured, and reliable to reason over.
Project Description / Key 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, reviewing, governing, and signing off on the ontological structures that AI systems in our programmes reason over.
- Design, develop, and govern enterprise ontologies, taxonomies, and knowledge graphs that accurately represent business domains, their relationships, and the rules that govern them.
- 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 (e.g. FIBO, BIAN, GS1, TM Forum) to meet organisation-specific semantic requirements.
- Develop and enforce semantic modelling standards, naming conventions, versioning, and curation workflows, and drive adoption of those standards across delivery teams.
- Enable AI and ML applications through knowledge graph enrichment, entity resolution, semantic search, and ontology-powered RAG pipelines.
- Engage business SMEs and domain experts to elicit and formalise implicit business rules, relationships, and concepts into explicit ontological structures.
Key Skills
- 5+ years of experience in knowledge engineering, ontology design, or semantic modelling, with a track record of owning the knowledge engineering approach on complex programmes, not just contributing to it.
- Proven deep expertise in ontology engineering, authoring OWL ontologies, RDFS schemas, SHACL constraint shapes, and SPARQL queries, with real enterprise delivery behind it.
- Hands-on experience with graph databases and knowledge graph platforms such as Neo4j, Amazon Neptune, Stardog, or GraphDB.
- Proficiency with semantic tooling including Protégé, TopBraid Composer, or equivalent ontology authoring environments.
- Strong understanding of how semantic models connect to downstream data products, metadata catalogues, and AI/ML enrichment workflows, and the ability to assure that integration is sound.
- Knowledge of property graph modelling and the 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, and practical experience applying them in enterprise contexts.
- Industry experience in Financial Services, Government, Health, Energy, or Utilities sectors in APAC is highly regarded.
- Good communication skills with the ability to engage both technical teams and business SMEs.
Benefits of working at Accenture:
· 18 weeks paid parental leave
· Long & short-term career break opportunities
· Structured career development program
· Local and international career opportunities.
· Certified as a Family Inclusive Workplace™
· Flexible Work Arrangements - centered around Accenture’s Truly Human ethos and our commitment to supporting the health and wellbeing of our people.
· We are proud to be in the top 3 of last year’s Diversity & Inclusion Index!
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We encourage applications from all people, and we are committed to removing barriers to the recruitment process and employee lifecycle. All employment decisions shall be made without regard to age, disability status, ethnicity, gender, gender identity or expression, religion or sexual orientation and we do not tolerate discrimination. If you require adjustments to the recruitment process or have a preferred communication method, please email [email protected] and cite the relevant Job Number, or contact us on +61 2 9005 5000.
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Skills Required
- 5+ years of experience in knowledge engineering, ontology design, or semantic modelling
- Experience owning knowledge engineering approaches on complex programmes
- Deep expertise authoring OWL ontologies, RDFS schemas, SHACL constraint shapes, and SPARQL queries
- Hands-on experience with graph databases and knowledge graph platforms such as Neo4j, Amazon Neptune, Stardog, or GraphDB
- Proficiency with Protege, TopBraid Composer, or equivalent ontology authoring tools
- Understanding of semantic model integration with data products, metadata catalogues, and AI/ML enrichment workflows
- Knowledge of RDF-based and property graph modelling paradigms
- Experience with entity resolution, semantic search, and knowledge-driven RAG architectures
- Experience with data mesh, data lakehouse, and federated governance models
- Knowledge of W3C linked data principles and LLM grounding techniques, including GraphRAG and ontology-grounded generation
- Industry experience in Financial Services, Government, Health, Energy, or Utilities sectors in APAC
- Strong communication skills with technical teams and business subject matter experts
Accenture Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Accenture and has not been reviewed or approved by Accenture.
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Healthcare Strength — Pay is considered competitive when paired with robust insurance options and other perks that compare well with large consulting and IT services peers. Multiple national medical plan options plus dental and vision are positioned as a core strength of the overall package.
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Retirement Support — Retirement support is positioned as a standout feature through a 401(k) dollar-for-dollar match up to a set percentage after eligibility. The package is reinforced by additional financial programs such as savings tools and related resources.
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Parental & Family Support — Parental and caregiving supports are presented as a meaningful benefit differentiator through substantial paid parental leave and multiple caregiver-oriented programs. Backup care and fertility/adoption/surrogacy navigation and reimbursements add breadth to family support beyond leave alone.
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