Lead Graph Data Engineer
First seen by Alion on Sep 26, 2026.
Role Overview:
We are looking for a Lead Graph Data Engineer to design and develop scalable Graph Database and Knowledge Graph solutions for banking use cases. The role will involve building graph-based data models, semantic layers and AI-enabled solutions while working closely with Data Engineering, Architecture, AI/ML, Risk, Compliance and Business teams.
Key Responsibilities:
- Design, develop and optimize Graph Database solutions using Neo4j.
- Develop complex and performance-optimized Cypher queries for graph traversal, analysis and data retrieval.
- Design graph data models, including nodes, relationships, properties, indexes and constraints.
- Build and maintain Knowledge Graphs to connect structured and unstructured banking data.
- Develop Ontologies, taxonomies and semantic models to represent business entities and relationships.
- Apply Semantic Web concepts, including RDF, OWL and SPARQL, where applicable.
- Develop data pipelines for ingestion, transformation, cleansing and integration of data into graph platforms.
- Write complex SQL queries for data extraction, transformation, validation and reconciliation.
- Integrate graph databases with enterprise data platforms, APIs, data lakes and other data sources.
- Leverage NLP, LLMs and RAG to develop graph-enabled GenAI and intelligent data solutions.
- Design Graph-enhanced RAG solutions combining Knowledge Graphs, embeddings and vector search.
- Support banking use cases including Customer 360, fraud detection, AML/KYC, risk analytics, transaction analysis, counterparty mapping and relationship intelligence.
- Ensure data quality, lineage, governance, security and scalability of graph solutions.
- Work with architects and technology teams to define enterprise graph and semantic data architecture.
- Lead technical design, PoCs and implementation of graph-based solutions.
- Mentor engineers and establish best practices for graph modelling, query optimization and data engineering.
Mandatory Skills:
- Strong hands-on experience in Neo4j and Cypher
- Expertise in Graph Databases and Graph Data Modelling
- Strong understanding of Knowledge Graphs
- Experience in Ontology / Ontology Modelling
- Strong SQL and data engineering skills
- Understanding of Semantic Technologies / Semantic Web
- Exposure to NLP, LLM and RAG
- Experience integrating multiple structured and unstructured data sources
- Strong understanding of data quality, governance and security
Skills
Neo4j, Knowledge Graph, SQL, Cypher Query Language, Data Modeling, LLM, RAG, NLP, Data Engineering, Ontology Engineering