A Data Engineer designs and maintains scalable data pipelines and storage systems, with a focus on integrating and processing knowledge graph data for semantic insights. They enable efficient data flow, ensure data quality, and support analytics and machine learning by leveraging advanced graph-based technologies. How Youll Make an Impact (responsibilities of role) Build and optimize ETL/ELT pipelines forknowledge graphsand other data sources. Design and manage graph databases (e.g., Neo4j, AWS Neptune, ArangoDB). Develop semantic data models using RDF, OWL, and SPARQL. Integrate structured, semi-structured, and unstructured data into knowledge graphs. Ensure data quality, security, and compliance with governance standards. Collaborate with data scientists and architects to support graph-based analytics. What You Bring (required qualifications and skills) Bachelors/masters in computer science, Data Science, or related fields.
Experience: 3+ years of experience in data engineering, with knowledge graph expertise.
Proficiency in Python, SQL, and graph query languages (SPARQL, Cypher).
Experience: with graph databases and frameworks (Neo4j, GraphQL, RDF).
Knowledge of cloud platforms (AWS, Azure). Strong problem-solving and data modeling skills. Excellent communication skills, with the ability to convey complex concepts to non-technical stakeholders. The ability to work collaboratively in a dynamic team environment across the globe.