Senior Knowledge Graph Engineer

Sobre el puesto

We are looking for a hands-on, production-focused Senior Knowledge Graph Engineer to join our growing AI Center of Excellence, responsible for using AI and machine learning to drive innovation across the organization. In this role, you will take the formal domain ontologies designed by our Knowledge Representation Architects and operationalize them into high-throughput, multi-hop systems. We welcome applications from European locations, with the possibility of remote work. Join us!
Your work will directly power autonomous AI agents that solve complex sustainability challenges — including decarbonisation, sustainable procurement compliance, and supply chain resilience. You will bridge the gap between unstructured sustainability disclosures and structured graph databases, building entity-resolution pipelines that make enterprise data agent-ready.
Your responsibilities will include (but will not be limited to):

Graph Infrastructure and Ingestion Pipelines

Design, implement, and maintain high-speed GraphRAG ingestion pipelines that transform relational data (ERP, SQL), unstructured ESG reports, and streaming feeds into operational Labeled Property Graphs (Neo4j, Memgraph) and RDF Triple Stores

A-Box Instantiation and Entity Resolution

Build automated Named Entity Recognition (NER), entity linking, and deduplication workflows to resolve mismatched vendor profiles, material SKUs, and facility coordinates into unified canonical graph nodes

Semantic Federation and External Data Integration

Implement automated ETL/ELT pipelines to map and federate internal supply chain data with external, open-source ontologies and registries (such as GLEIF for corporate ownership, W3C SSN/SOSA for IoT sensors, and Copernicus for geo-hazard alerts, PROV-O for data provenance)

GraphRAG and Agent Tooling

Partner with AI/ML Engineers to build low-latency GraphRAG retrieval layers—writing optimized Cypher and SPARQL queries, implementing NL2Query tools for agents, hybrid vector-graph indexing pipelines, and Model Context Protocol (MCP) tool endpoints for autonomous LLM agents

Deterministic Guardrails and Pipeline Validation

Operationalize SHACL (Shapes Constraint Language) shapes into automated data quality tests within CI/CD pipelines to prevent hallucinated or non-compliant data mutations from entering the enterprise knowledge graph

Performance Optimization and GraphOps

Optimize multi-hop query performance, graph partitioning, and database indexing strategies to handle sub-second traversal over billions of nodes and edges

Degree in Computer Science, Mathematics, Engineering, or a related technical discipline

4+ years of production experience building and querying graph databases, specifically Labeled Property Graphs (Neo4j, Memgraph, TigerGraph) or RDF Triple Stores (GraphDB, Stardog, Virtuoso)

Strong experience in cloud technology, preferably Azure and its ecosystem (e.g., Azure Foundry, Azure Bicep, AzureML and Azure Cloud Storage)

Advanced proficiency in Python (RDFLib, NetworkX, PyGraphistry) for building scalable, production-grade data pipelines

Experience building entity extraction pipelines using modern NLP frameworks (LangChain, LlamaIndex, spaCy) or LLM-based structured extraction

Hands-on experience with modern data transformation tools (dbt) and integrating graph databases with vector stores (Qdrant, Pinecone, pgvector) for hybrid search architectures

Solid understanding of semantic web standards (RDF, RDFS and OWL, SKOS, SHACL, RDF-star, SPARQL), graph schema design principles (T-Box vs. A-Box separation), and mapping languages for dealing with heterogeneous data structures (RML, R2RML)

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

Direct experience building Model Context Protocol (MCP) servers to expose graph tools to LLM agents is a plus

Experience with enterprise OBDA approaches at-scale is a plus

Offer available only for candidates eligible to work and live in Spain

Location: Hybrid in Barcelona (4 days per month in the office) / Full remote from Spain

In return for your expertise, we offer:

Support with all the necessary office and IT equipment

Flexible working hours

Wellness allowance for mental and physical wellbeing

Access to professional mental health support

Referral bonus policy

Learning and development

Sustainability events and community involvement

Peer recognition program

Employee-led resource groups

Remote work from abroad policy

Meals and Transportation Vouchers (Coverflex card)

Dental Benefits

Life & Accident Insurance + Private Health Insurance

Paid employee volunteer day

Paid moving day (1/year)

Time off: 1 Community Service Day + 1 Personal Day

Summer Hours in July and August (36 hours per week)

Hybrid Monthly Allowance for electricity and Internet

Our hiring team looks forward to reviewing your CV, in English, with a guaranteed response to every application. A new job with purpose awaits you!
Don’t fit all the criteria but still think you’d be a good candidate? Please apply anyway to give our hiring team the opportunity to assess your skills and to learn more about what you could bring to EcoVadis. We’re interested in hiring from a diverse and skilled talent pool, regardless of professional and educational background.
Can the hiring process be adjusted to suit my needs? Yes. We want everyone going through the hiring process with EcoVadis to feel confident that you are able to demonstrate your full potential. We welcome applications from disabled people, people with long-term health conditions, and neurodiverse candidates. If you need any adjustments, including the provision of interview questions, please let the hiring team know.
Our team’s strength comes from everyone’s uniqueness and is founded upon mutual respect. EcoVadis commits to equity, inclusion and reducing bias in our hiring processes. EcoVadis does not accept any form of…