Job Description
Full time position
Location : Stuttgart Germany
Key Responsibilities
· Design and develop scalable graph data models (nodes, edges, properties) based on network architecture and system relationships.
· Implement and manage Oracle Property Graph solutions within the Oracle Database ecosystem.
· Convert relational and network data into graph structures for advanced analytics.
· Develop and optimize graph queries using PGQL (Property Graph Query Language)
· Analyze and interpret network topology, connectivity, and dependencies using graph techniques.
· Collaborate with data architects, DBAs, and application teams to integrate graph solutions.
· Ensure performance tuning, scalability, and efficient data processing for large graph datasets.
· Support data migration, transformation, and validation processes.
· Provide technical guidance and best practices for graph-based implementations.
Required Skills & Qualifications
· 7–9+ years of strong experience in Oracle Database development and administration.
· Hands-on experience with Oracle Property Graph and related tools (Graph Server, Graph Studio).
· Strong expertise in SQL, PL/SQL, and Oracle data architecture.
· Proven experience in data modeling, including translating relational models into graph models.
· Experience working with network-based data structures (telecom, infrastructure, or similar domains).
· Strong understanding of graph concepts such as traversal, pathfinding, and relationship analysis.
· Ability to design efficient and scalable graph schemas.
Requirements
Key Responsibilities • Design and develop scalable graph data models (nodes, edges, properties) based on network architecture and system relationships. • Implement and manage Oracle Property Graph solutions within the Oracle Database ecosystem. • Convert relational and network data into graph structures for advanced analytics. • Develop and optimize graph queries using PGQL (Property Graph Query Language) • Analyze and interpret network topology, connectivity, and dependencies using graph techniques. • Collaborate with data architects, DBAs, and application teams to integrate graph solutions. • Ensure performance tuning, scalability, and efficient data processing for large graph datasets. • Support data migration, transformation, and validation processes. • Provide technical guidance and best practices for graph-based implementations.