Who are we?
CLEVR delivers digital transformation at scale by implementing Siemens and Mendix solutions to serve industries like manufacturing, retail, energy, and more. We leverage PLM, MOM/MES, and low-code technologies for manufacturing optimization and business process automation while ensuring seamless integration with other core systems like SAP, IBM, and Salesforce. CLEVR brings together technology and industry expertise to provide strategic solutions that streamline operations, drive efficiency, and enable digitalization to fit market demands.
About the job:
Are you a consultant who knows how to turn complex enterprise data into governed, connected knowledge?
As a Consultant Knowledge Graph, you’ll design and build knowledge graph solutions on the Siemens stack, including Rapidminer Graph Studio and Graph Lakehouse, part of Siemens Intelligence Center X. You’ll work with customers and colleagues to onboard data, model ontologies, build graphmarts, and turn business requirements into practical solutions.
You’ll also help customers explore how knowledge graphs can support trustworthy AI use cases, including RAG and LLM applications.
What makes this role unique:
This role combines data modelling, technical delivery, and customer advisory work.
You’ll work across the full knowledge graph lifecycle while helping customers create trusted, reusable data foundations for both business and AI use cases. It’s a role for someone who enjoys ownership, learning, and solving complex data challenges in close collaboration with customers and colleagues.
Your role will include:
Design and build knowledge graphs on the Siemens stack: onboard data, model ontologies, build graphmarts and write SPARQL queries, working in delivery teams.
Onboarding data from databases, files and documents with Graph Studio, using the Graph Data Interface in Graph Lakehouse.
Model business concepts with domain experts: glossaries, taxonomies and ontologies in RDFS, OWL and SKOS.
Gather requirements in workshops. Turn them into user stories and acceptance criteria.
Validate and tune the results: SPARQL and SQL checks, query tuning on Graph Lakehouse, user acceptance and training.
Publish the graph to consumers (dashboards, query endpoint, OData) and manage access. Move work from dev to test to prod.
Build and test LLM and RAG use cases on the knowledge graph (this is the full, ongoing part of the role).
Advise customers on what is possible and sensible.
Work autonomously in Agile teams. Take ownership, deliver what you promise, and share what you learn with newer colleagues.
What you bring to the table:
Bachelor's degree (IT, data, business or comparable).
3+ years with knowledge graph platforms, such as Rapidminer Graph Studio and Graph Lakehouse (formerly Altair Graph Studio / Graph Lakehouse, and before that Anzo / AnzoGraph DB), Stardog, Amazon Neptune, Neo4j, TigerGraph or Ontotext GraphDB. At least 6 months of that hands-on with the Siemens stack under any of its names.
Solid knowledge of RDF, RDFS and OWL. SPARQL 1.1 in practice, including named graphs and property paths.
Working knowledge of SQL and relational data modelling, and the ability to map it onto an ontology.
Able to sit with a domain expert, ask the right questions, turn the answers into a model
Basic understanding of LLMs and prompt engineering is an advantage.
SHACL, SKOS, Turtle by hand, REST APIs for scripting graphmarts and migration packages are an advantage.
Familiarity with Mendix or another low-code platform is an advantage; no certification required.
Domain knowledge in manufacturing or product lifecycle is an advantage.
Applies SCRUM/Agile and follows the company's best practices.
Fluent in English, verbally and in writing. Other languages, like Dutch, German or Norwegian are a plus.
What you’ll get:
Competitive salary
Annual leave: 30 vacation days
Work model: Hybrid
Company car
Hansefit Subscription
Your devices: laptop, mobile phone, and accessories
Learning and development:…