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Job description

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 You’ll Make an Impact (responsibilities of role) Build and optimize ETL/ELT pipelines for knowledge graphs and 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) Bachelor’s/master’s 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.
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