17 дней назад
Knowledge Engineer (Knowledge Graphs)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Knowledge Engineer (Knowledge Graphs) (RDF/OWL/SKOS): Designing enterprise ontologies and knowledge graphs that enable AI systems to reason across commercial data domains with an accent on formal knowledge representation, semantic modeling, and governance. Focus on capturing business logic, defining semantic boundaries, and building scalable structures for conversational analytics, AI agents, and cross-domain reasoning.
Location: Cologne, Germany
Company
delivers digital transformation projects and tailored consulting solutions for the life sciences industry.
What you will do
- Design and build enterprise ontologies, entity hierarchies, relationship types, inference rules, and knowledge graphs.
- Translate business definitions and data models into machine-readable representations using RDF, OWL, and related standards.
- Work with subject matter experts to capture domain knowledge, business logic, ontologies, and taxonomies.
- Maintain clear boundaries between ontologies, semantic data models, and knowledge graphs in collaboration with data modelers and semantic engineers.
- Align knowledge assets with semantic web standards and governance guidelines.
- Enable conversational analytics, AI agents, and cross-domain reasoning through reusable and scalable knowledge structures.
Requirements
- 3–5 years of experience in engineering, semantic modeling, or information and knowledge management.
- Hands-on experience with ontology and taxonomy modeling, enterprise ontologies, and knowledge graphs.
- Proficiency in RDF, OWL, SKOS, graph databases, knowledge graph platforms such as Stardog or AWS Neptune, and SPARQL.
- Ability to work with subject matter experts and convert business definitions into machine-readable structures.
- Strong communication, problem-solving, stakeholder management, ownership, and accountability skills.
- Strong spoken and written English is required.
Nice to have
- Experience with Stardog, AWS Neptune, or similar knowledge graph platforms.
- Knowledge of regulatory requirements, data governance practices, and industry trends.
Culture & Benefits
- Collaborative, flat-structured environment with cross-functional teamwork and global colleagues.
- Annual training budget, regular workshops, and professional development opportunities.
- Support with visas, permits, and international assignments.
- Benefits and perks tailored to the country of residence.
- Competitive salary and benefits package, plus an employee referral program.
Hiring process
- Submit a CV followed by a profile review by Talent Acquisition.
- Attend an introductory call and a technical interview.
- Some roles may include a client interview before final feedback.
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