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.