Data engineer in knowledge graphs

Join a dynamic ecosystem where the future of business is created and experienced every day. Be part of this transformation! At LUZA Group, passion, perseverance, and the desire to push boundaries define our path to success. Founded in 2006, we are a Portuguese multinational with more than 1,200 talented professionals and a turnover exceeding €30 million.

• Define and maintain Procurement ontologies, covering entities, attributes, relationships, events, states, and business concepts.
• Take responsibility for the semantic model of key domains, such as suppliers, contracts, obligations, sourcing events, categories, risks, savings, and operational processes.
• Design and evolve Procurement Knowledge Graphs, representing entities, relationships, dependencies, events, and business context.
• Define Context Graph patterns that bring together relevant information for users, workflows, information retrieval systems, and Artificial Intelligence agents.
• Explicitly model temporal relationships, lifecycle states, data provenance, hierarchies, responsibilities, and dependency structures.
• Define graph construction patterns that link structured data, documents, communications, workflow events, and external signals to canonical entities.
• Establish approaches for Entity Resolution, supplier normalization, deduplication, identity management, and assessing the confidence level of relationships.
• Define validation rules and quality criteria for ontology and graph structures.
• Ensure that semantic models and graphs support information retrieval (Retrieval), reasoning, recommendations, workflow automation, and autonomous execution by AI agents.
• Collaborate with the Data Architecture, Data Engineering, Product, Artificial Intelligence, Domain, and Governance teams, ensuring that graph structures are technically feasible, properly governed, and suited to business needs.
• Reduce the duplication of business logic in dashboards, applications, and workflow tools by centralizing business meaning and rules in shared semantic models and graphs.

• Experience in semantic modeling, ontology design, knowledge graphs, graph modeling, or business domain modeling.
• Strong knowledge of entities, relationships, events, lifecycle states, and business context.
• Ability to translate complex Procurement concepts into reusable semantic structures and graphs.
• Knowledge of graph databases, RDF and Property Graph concepts, ontologies, taxonomies, and knowledge representation.
• Knowledge of Entity Resolution, normalization, provenance, lineage, and metadata management.
• Ability to design models that support both human interpretation and automated reasoning by machines.
• Ability to collaborate easily with Data Engineering and Architecture teams, Product teams, domain specialists, and Artificial Intelligence Engineering teams.
• High attention to rigor, consistency, quality, and the long-term sustainability of semantic models.

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