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.