5 days ago

Semantic Data Expert

AGL

Docklands

5 days ago

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AGL is seeking a Semantic Data Expert to join their Data & AI Value & Transformation team in Docklands, Victoria, Australia. The role involves designing and stewarding the enterprise semantic layer, including semantic models, business glossary, taxonomies, ontologies, and knowledge graphs, to make data AI-ready. The ideal candidate has experience in semantic data modelling, knowledge of RDF, OWL, SKOS, SPARQL, and strong SQL skills.

AI-enabledHybridFull-timeEntry LevelSemantic Data ModellingData Modelling

Semantic Data Expert

Apply

AI-enabledHybridFull-timeEntry LevelSemantic Data Modelling

Salary

Not specified

Work Location

Docklands, Victoria, Australia, AU

Work Model

Hybrid

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

Semantic Data ModellingData ModellingInformation Architecturedbt Semantic LayerPower BIAnalysis ServicesCubeAtScaleOntologiesTaxonomiesKnowledge GraphsRDFOWLSKOSSPARQLSQLSnowflakeDatabricksAzureData PipelinesMetadata ManagementData GovernanceData CataloguingBusiness GlossaryRAGLLM GroundingSemantic SearchVector Search

Soft Skills

CommunicationCollaborationProblem SolvingStakeholder ManagementContinuous Improvement

Key Responsibilities

•Design, build and steward AGL’s enterprise semantic layer – semantic and metric models, business glossary, taxonomies and ontologies – so that key business terms and metrics carry a single, agreed definition.
•Translate business concepts and questions into reusable semantic data models over the Enterprise Data Platform, working with data engineers to align physical data structures to agreed business meaning.
•Develop and maintain knowledge graphs and semantic relationships that connect data across domains (customer, energy markets, assets and retail) to improve data discoverability and reuse.
•Curate the semantic definitions, context and metadata that make enterprise data ‘AI-ready’, grounding generative AI, retrieval-augmented generation (RAG) and AI agents in trusted business meaning.
•Partner with Data Governance to embed semantic standards, data definitions and metadata management into the enterprise data catalogue and governance framework.
•Enable trusted self-service analytics by providing consistent, well-documented semantic models that business users and analysts can consume with confidence.
•Act as the subject-matter expert on semantic modelling, advising delivery squads and business unit teams on best-practice data definitions, modelling patterns and tooling.
•Track emerging standards in semantic technology, ontologies and AI grounding, and champion continuous improvement of AGL’s semantic tooling and practices.

Semantic DataData ModellingKnowledge GraphsOntologiesTaxonomiesAI-readyData GovernanceHybridFull-timeEnergy

Core Qualifications

Technical (Must-have)

Soft Skills

CommunicationCollaborationProblem SolvingStakeholder ManagementContinuous Improvement

Key Responsibilities

•Design, build and steward AGL’s enterprise semantic layer – semantic and metric models, business glossary, taxonomies and ontologies – so that key business terms and metrics carry a single, agreed definition.

•Translate business concepts and questions into reusable semantic data models over the Enterprise Data Platform, working with data engineers to align physical data structures to agreed business meaning.

•Develop and maintain knowledge graphs and semantic relationships that connect data across domains (customer, energy markets, assets and retail) to improve data discoverability and reuse.

•Curate the semantic definitions, context and metadata that make enterprise data ‘AI-ready’, grounding generative AI, retrieval-augmented generation (RAG) and AI agents in trusted business meaning.

•Partner with Data Governance to embed semantic standards, data definitions and metadata management into the enterprise data catalogue and governance framework.

•Enable trusted self-service analytics by providing consistent, well-documented semantic models that business users and analysts can consume with confidence.

•Act as the subject-matter expert on semantic modelling, advising delivery squads and business unit teams on best-practice data definitions, modelling patterns and tooling.

•Track emerging standards in semantic technology, ontologies and AI grounding, and champion continuous improvement of AGL’s semantic tooling and practices.