Knowledge Manager

The key requirements we are looking for are: Experience in knowledge architecture and governance, data governance, or enterprise data management. This implies experience defining conceptual architectures, domain boundaries, governance models, and lifecycle controls. Solid knowledge of ontologies, Knowledge Graphs, semantic models, metadata, and knowledge lifecycle management. Understanding of Semantic Linking and the relationship between conceptual knowledge and physical data assets. Experience establishing frameworks for ownership, validation, provenance, versioning, and quality.

We are looking for a person with the ability to translate organizational strategy and business needs into a coherent knowledge architecture, facilitating decisions that involve multiple domains or organizational areas.

At Reale ITES, we offer the experience and stability that only a major company with a strong track record can provide. The workplace will be at our office in central Madrid, with full-time hours, depending on the time of year, and remote work several days a week. We offer a permanent contract with an attractive salary and excellent social benefits. Reale Seguros holds the top recognitions for being a great place to work: Great Place to Work, Family-Responsible Company, Equality in the Workplace, and Flexible Hours Seal.

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What is it like to work at Reale ITES?

At Reale ITES, we are looking for a Knowledge Manager profile to lead the definition, governance, and evolution of the organization's semantic knowledge architecture.

Main purpose:

The primary mission of the Knowledge Manager will be to ensure that semantic knowledge is managed as a governed organizational asset, with clear ownership, approved business meaning, a consistent architecture, and controlled evolution. It provides Ontology Engineers, Data Product teams, and other authorized consumers with a governed framework appropriate to the organizational scope, whether at the Group level, company-specific, country-specific, departmental, domain, or initiative level.

Knowledge architecture: Define the target architecture, organize knowledge domains, and maintain alignment between semantic assets, data, and artificial intelligence systems.

Knowledge governance: Establish the governance framework, lifecycle controls, and ownership requirements, ensuring the assignment of Data Owners.

Ontological direction and portfolio evolution: Set ontology modeling principles, review technical designs, and coordinate portfolio evolution according to business value.

Knowledge Graph Governance: Define the role, quality and access requirements, and architectural compliance of knowledge graphs.

Tools and enablement: Determine the functional and governance requirements for supporting tools, fostering their adoption and correct use.

Semantic knowledge for artificial intelligence: Establish the mechanisms for the exposure and consumption of semantic knowledge by AI, guaranteeing the traceability and validation of automated proposals.