• Proven graph data modeling — you can explain when to use a node vs. a relationship vs. a property, and how to model time, hierarchies and versioning.
• Practical knowledge of knowledge graph concepts: ontologies and taxonomies, entity resolution, schema design, and how property graphs compare with RDF/SPARQL.
• Proficiency in Python (preferred) or Java, including the official Neo4j drivers.
• Experience building ETL/ELT pipelines and working with SQL databases and at least one cloud platform (AWS, Azure or GCP).
• Hands-on use of Neo4j Graph Data Science algorithms on a real dataset.
• Familiarity with Git, CI/CD, Docker and writing automated tests.
• Transparent communication: able to explain graph designs to non-graph engineers and business stakeholders.
• Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
📌 Data Ontology Bengaluru
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📍 Bengaluru
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