Job description
About the Role
We are seeking a Graph Database & Knowledge Graph Architect with strong Neo4j and Data Engineering expertise to design, build, and scale enterprise-grade graph data platforms and knowledge graph solutions. The ideal candidate will have experience in graph data modeling, large-scale data integration, ETL/ELT pipelines, and advanced analytics architectures.
Experience: 7–15 Years Location: New Delhi Key Responsibilities Design and implement scalable Neo4j graph database architectures and Knowledge Graph solutions. Develop graph data models, schemas, ontologies, and relationship frameworks. Build and optimize ETL/ELT pipelines to ingest, transform, and enrich data from multiple structured and unstructured sources.
Design data integration frameworks connecting graph databases with relational, NoSQL, and big data platforms. Optimize Cypher queries, graph traversals, indexing, and database performance. Ensure data quality, governance, security, and lifecycle management. Collaborate with Data Engineering, AI/ML, and Product teams to deliver connected intelligence solutions.
Support advanced analytics, entity resolution, relationship discovery, and Graph AI use cases.
Requirements
Required Skills 7+ years of experience in Data Engineering, Data Architecture, or Database Engineering. Strong hands-on expertise in Neo4j and Graph Database technologies. Advanced proficiency in Cypher Query Language. Experience with Knowledge Graph Architecture and Graph Data Modeling. Strong understanding of Data Engineering concepts, including ETL/ELT, data pipelines, data integration, and data warehousing.
Proficiency in Python, SQL, and data processing frameworks. Experience working with large-scale datasets and distributed data systems. Knowledge of cloud platforms (AWS, Azure, or GCP).
Preferred Skills
Neo4j Graph Data Science (GDS). Apache Spark, Kafka, Airflow, or similar data engineering tools. RDF, OWL, SPARQL, and Semantic Web technologies. GraphRAG, LLM integration, and AI-powered Knowledge Graph solutions. Experience in Cyber Security, Fraud Analytics, Intelligence, or Investigative Analytics domains. Qualification Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related field.