Position Summary:
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.