Neo4j Architect
Summary
Architect role at Innefu Labs (New Delhi) designing and scaling enterprise Neo4j graph databases and knowledge graphs: building graph data models and ontologies, ETL/ELT pipelines, optimizing Cypher queries, and integrating graph data with AI/ML analytics. Requires 7-15 years in data/database engineering.
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.