Overview

As Senior Knowledge Graph Engineer, you will operationalize domain ontologies into high-throughput graph systems powering autonomous AI agents for sustainability challenges. You'll bridge unstructured disclosures and structured graphs, building scalable pipelines and entity resolution to create enterprise-ready data. You'll collaborate across AI and data teams to enable real-time insights in decarbonisation, sustainable procurement, and supply chain resilience.

This role offers hands-on impact at the AI Center of Excellence shaping how EcoVadis uses AI for general sustainability.

Compensaciones / Beneficios Remote work from Spain

Flexible working hours

Wellness allowance

Mental health support

Learning and development

Private Health Insurance

Responsabilidades Design, implement, and maintain high-speed GraphRAG ingestion pipelines for relational, unstructured, and streaming data into labeled property graphs and RDF stores

Develop automated NER, linking, and deduplication workflows to resolve vendor profiles, SKUs, and coordinates into canonical graph nodes

Enable semantic federation by ETL/ELT pipelines to map internal data with external ontologies and registries (GLEIF, W3C SSN/SOSA, Copernicus, PROV-O)

Collaborate to build low-latency GraphRAG retrieval layers, write optimized Cypher and SPARQL queries, and support NL2Query for agents





Operationalize SHACL shapes in CI/CD data quality tests to prevent non-compliant data mutations

Optimize multi-hop query performance, partitioning, and indexing for sub-second traversal over billions of nodes and edges

Requisitos principales Degree in Computer Science, Mathematics, Engineering, or related technical discipline

4+ years of production experience with graph databases (Neo4j, Memgraph, TigerGraph) or RDF stores (GraphDB, Stardog, Virtuoso)

Strong cloud experience, preferably Azure ecosystem

Advanced Python (RDFLib, NetworkX, PyGraphistry)

Experience with NLP frameworks for entity extraction (LangChain, LlamaIndex, spaCy) or LLM-based extraction

Experience with dbt and integrating graphs with vector stores (Qdrant, Pinecone, pgvector) for hybrid search

Solid knowledge of semantic web standards (RDF, RDFS, OWL, SKOS, SHACL, SPARQL) and data modeling (RML, R2RML)

Experience with domain-specific supply chain, carbon accounting (GHG Protocol), or lifecycle data is a plus

Experience building MCP servers to expose graph tools to LLM agents is a plus

Experience with enterprise OBDA approaches at scale is a plus

Collaborative, cross-functional communication

Structured problem solving

Attention to data quality and reproducibility

Neo4j, Memgraph, TigerGraph

GraphDB, Stardog, Virtuoso

Cypher, SPARQL

📌 Senior Knowledge Graph Engineer (Barcelona)
🏢 Ecovadis
📍 Barcelona