A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience
Role Overview:
We are seeking a Graph Database SME to architect and implement advanced graph-based data models and analytics capabilities within a large banking data platform. The candidate will be responsible for designing scalable graph solutions to uncover hidden relationships, improve customer intelligence, detect fraud networks, and enhance compliance visibility.
Key Responsibilities:
· Design and implement property graph or RDF-based data models to capture complex entity relationships (e.g., customer–account–address–device–transaction).
· Work with data architects to translate relational data models to graph structures suitable for graph traversal and inference.
· Deploy, configure, and optimize graph database platforms such as Neo4j, DGraph
· Ingest data from Cloudera/HDFS, RDBMS, or real-time Kafka streams into the graph store.
· Develop complex graph queries using Cypher, Gremlin, or SPARQL for relationship discovery, pattern matching, and path analysis.
· Build use cases for CIF resolution, fraud rings, KYC hierarchies, risk propagation, ,influence networks.
· Expose graph APIs or integrate with downstream applications and BI/ML platforms for analytics consumption.
Experience: 6+ years
Graph Database Fundamentals: Understanding graph structures, nodes, edges, and relationships.
Query Languages: Familiarity with SPARQL (for RDF-based GraphDB) or Cypher (for Neo4j).
Database Management: Experience with database setup, indexing, and optimization.
Programming Skills: Proficiency in languages like Python, Java, or JavaScript for database interaction.
Data Modeling: Ability to design efficient graph schemas and relationships.