Neo4j / Knowledge Graph Engineer

About the Role

Looking for an experienced Knowledge Graph / Neo4j engineer to design, implement and operate graph-based data platforms and integrations. The role involves graph data modelling, building ETL pipelines, and collaborating with data engineering and business teams.

Technical Skills (Must-have)

- 4–7+ years of experience in knowledge graphs, semantic technologies, or graph databases. - Expert-level experience with Neo4j: Cypher, Neo4j Desktop, Bloom, and Graph Data Science (GDS). - Strong understanding of graph modelling, graph theory, and ontology design. - Hands-on programming with Python, Java, or Scala for data integration and automation. - Experience with ETL platforms and streaming systems such as Kafka and Spark. - Familiarity with API design, microservices architecture, and deploying Neo4j in cloud environments.

Preferred / Nice-to-have

- Experience with RDF, OWL and SPARQL (for hybrid graph ecosystems). - Experience integrating Neo4j or graph stores with LLMs, vector embeddings or similarity search stacks. - Hands-on cloud experience (AWS, GCP, Azure) and familiarity with Neo4j Aura. - Containerization and orchestration experience: Docker, Kubernetes and CI/CD pipelines.

Soft Skills

- Strong analytical and problem-solving abilities. - Ability to communicate complex graph concepts to non-technical stakeholders. - Collaborative mindset with experience working across data, engineering and business teams.

Mandatory

- Relevant hands-on Neo4j project experience. - Able to produce sample data models or explain ontology choices during interview.