Senior Knowledge Graph Engineer - Remote/Hybrid (Spain)

Ecovadis-; Barcelona; Híbrido; EUR 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Wellness allowance

Private health insurance

Remote work from abroad policy

Meals & Transportation vouchers

Learning & development

Descripción de la vacante

EcoVadis is seeking a hands-on Senior Knowledge Graph Engineer to operationalize ontologies into high-throughput graph systems. You will influence data pipelines powering autonomous AI agents addressing sustainability challenges, including decarbonisation and responsible procurement.

You will bridge structured and unstructured data, build entity-resolution pipelines, and collaborate with AI/ML teams to deliver low-latency graph retrieval and validation.

Formación

• Degree in Computer Science, Mathematics, Engineering, or a related technical discipline.
• 4+ years of production experience building and querying graph databases (Labeled Property Graphs or RDF stores).
• Strong experience in cloud technology, preferably Azure.
• Advanced Python for scalable data pipelines (RDFLib, NetworkX).
• Experience with NLP frameworks (LangChain, LlamaIndex, spaCy) and LLM-based extraction.
• Hands-on with data transformation tools (dbt) and integrating graph databases with vector stores (Qdrant, Pinecone, pgvector).
• Solid understanding of semantic web standards (RDF, RDFS, OWL, SKOS, SHACL, SPARQL) and graph schema design (T-Box/A-Box).
• Experience with supply chain, carbon accounting, or LCA data structures is a plus.
• Experience building MCP servers to expose graph tools to LLM agents is a plus.

Responsabilidades

• Graph Infrastructure and Ingestion Pipelines: build high-speed GraphRAG pipelines and ingest data into graph databases and RDF stores.
• A-Box Instantiation and Entity Resolution: develop NER, linking, and deduplication to canonical graph nodes.
• Semantic Federation: map internal data to external ontologies and registries (GLEIF, W3C SSN/SOSA, Copernicus).
• GraphRAG and Agent Tooling: optimize NL2Query, hybrid vector-graph indexing, MCP endpoints for autonomous agents.
• Deterministic Guardrails: encode SHACL shapes into CI/CD data quality tests to prevent bad data.
• Performance Optimization: improve multi-hop queries, partitioning, and indexing.

Conocimientos

Graph databases

Python

NLP frameworks

LangChain

spaCy

LyraIndex/LlamaIndex

dbt

vector stores

Cypher/SPARQL

MCP servers

Educación

B.S. or higher in CS/Engineering

Herramientas

Neo4j

Memgraph

TigerGraph

GraphDB

Stardog

Virtuoso

Azure cloud

Qdrant

Pinecone

pgvector

Descripción del empleo

EcoVadis is seeking a hands-on Senior Knowledge Graph Engineer to operationalize ontologies into high-throughput graph systems. You will influence data pipelines powering autonomous AI agents addressing sustainability challenges, including decarbonisation and responsible procurement.

You will bridge structured and unstructured data, build entity-resolution pipelines, and collaborate with AI/ML teams to deliver low-latency graph retrieval and validation.