GraphDB Specialist / Data Engineer Neo4j & Knowledge Graph (Göteborg)

About the Role We are looking for an experienced GraphDB Specialist (Data Engineer) to design, develop and maintain a central Knowledge Graph data foundation for a Cybersecurity Data Collection and Correlation (CDC) Engine. In this role, you will work with complex data structures, security-related entities and relationships, building scalable graph database solutions. You will also contribute to integrating graph data with AI and Large Language Model (LLM) pipelines using GraphRAG and vector-graph hybrid querying. You will collaborate with technical teams to develop reliable data architecture, automate ingestion workflows and ensure secure and efficient access to graph data. Key Responsibilities Design and develop Knowledge Graph architecture, ontology and data models. Build and maintain graph data ingestion pipelines. Implement GraphRAG and vector-graph hybrid querying to integrate graph data with LLM-based applications. Develop and manage graph database solutions using Neo4j and Azure Cosmos DB (Gremlin). Integrate data ingestion and graph update workflows into CI/CD pipelines. Manage graph database configurations, updates and data relationships. Ensure data quality, consistency, scalability and secure access to graph information. Collaborate with engineering, AI and cybersecurity teams. Required Qualifications Strong hands-on experience with graph databases, particularly Neo4j. Experience with Azure Cosmos DB and Gremlin API. Strong background in data engineering and data modelling. Experience designing and developing Knowledge Graphs and ontologies. Experience building and maintaining data ingestion pipelines. Knowledge of CI/CD processes and integration of data workflows into automated pipelines. Understanding of graph querying, database architecture and data relationships. Good communication and collaboration skills. Professional proficiency in English. Preferred Qualifications Experience with GraphRAG and Retrieval-Augmented Generation (RAG). Experience integrating graph databases with LLM applications. Knowledge of vector databases and hybrid search solutions. Experience in cybersecurity, threat intelligence or security data analytics. Experience with cloud-based data engineering solutions.