Salary: £? - ? per year Requirements: Bachelors or masters degree in computer science, Data Science, Engineering, or a related field. 3 years of experience in data engineering, with strong exposure to knowledge graph technologies. Strong proficiency in Python and SQL. Experience with graph query languages such as SPARQL and Cypher. Hands-on experience with graph databases and frameworks such as Neo4j, GraphQL, RDF, or similar. Experience working with cloud platforms such as AWS and/or Azure. Strong data modelling, analytical, and problem-solving skills. Excellent communication skills with the ability to explain complex technical concepts clearly. Proven ability to work collaboratively in distributed, global teams. Desirable: experience with large-scale distributed data systems. Desirable: familiarity with machine learning pipelines and graph analytics. Desirable: understanding of data governance, metadata management, and semantic technologies. Desirable: experience working in Agile delivery environments. Responsibilities: Build and optimise ETL/ELT pipelines for knowledge graphs and other data sources. Design and manage graph databases such as Neo4j, AWS Neptune, and ArangoDB. Develop semantic data models using RDF, OWL, and SPARQL. Integrate structured, semi-structured, and unstructured data into knowledge graph systems. Ensure data quality, security, and compliance with governance standards. Collaborate with data scientists and architects to support graph-based analytics and machine learning use cases. Monitor, troubleshoot, and enhance data pipelines for performance and reliability. Contribute to best practices in data engineering, documentation, and data architecture standards. Technologies: AWS ArangoDB Azure Cloud ETL GraphQL Support Machine Learning Neo4J Python RDF SQL Security AI More: We are a global technology and engineering organisation at the forefront of digital transformation, industrial innovation, and intelligent infrastructure. This is a fully remote, 6-month contract role, ideally suited to UK-based candidates, offering the chance to work on cutting-edge data platforms and knowledge graph solutions that support complex real-world challenges across multiple industries. You will join an international, collaborative, inclusive team and gain exposure to advanced data engineering technologies, with opportunities for professional development, learning, and flexible working arrangements to support work-life balance. last updated 24 week of 2026