Associate Staff Engineer (Graph Data Engineer)

Job Purpose

Apply deep expertise in Tiger Graph, graph analytics, and graph-based machine learning to architect and implement enterprise-scale graph platforms and advanced analytic engines on AKS Kubernetes, enabling high-performance, relationship-driven intelligence and providing expert guidance on graph-driven AI solutions.

Job Responsibilities

• Lead the design and development of advanced graph data models, graph algorithms, and graph-based machine learning solutions to unlock complex relationship insights and enterprise value.
• Translate highly connected and complex data into actionable business solutions using TigerGraph and graph analytics techniques within financial services contexts.
• Architect, deploy, and operate scalable Tiger Graph clusters on AKS Kubernetes, ensuring high availability, fault tolerance, and optimal resource utilisation.
• Drive the operationalisation of graph-based analytics and machine learning use cases, ensuring production robustness, scalability, and alignment with business objectives.
• Design, build, and manage distributed graph infrastructure on Kubernetes, including containerisation, orchestration, autoscaling, and cluster management.
• Implement secure and performant data ingestion pipelines into TigerGraph from enterprise data platforms (e.g. ADLS, Databricks), supporting batch and real-time processing.
• Configure and manage networking, storage, and security for graph workloads on AKS, including integration with enterprise identity, access control, and secrets management.
• Optimise graph query performance (GSQL), workload isolation, and system throughput across large-scale distributed environments.
• Apply advanced graph techniques such as graph neural networks, link prediction, community detection, and path analysis to solve high-impact use cases.
• Build and manage enterprise knowledge graphs, enabling advanced analytics, GenAI, and RAG capabilities grounded in relationship-centric data.
• Enable feature engineering and reuse through graph-derived features, enhancing downstream machine learning models and decisioning systems.
• Deliver high-impact graph analytics solutions across fraud detection, financial crime, customer intelligence, and network risk management.
• Oversee end-to-end graph solution architecture, ensuring seamless integration with data platforms, APIs, and enterprise systems.
• Develop CI/CD pipelines for graph applications and infrastructure using Kubernetes-native and DevOps tooling, enabling automated deployment and monitoring.
• Provide thought leadership on graph and Kubernetes strategy, embedding scalable graph capabilities into enterprise AI platforms.
• Mentor teams on graph modelling, GSQL development, Kubernetes operations, and graph-based ML techniques.
• Continuously monitor and optimise system health, cluster performance, cost efficiency, and model accuracy in dynamic environments.
• Evaluate emerging tools across graph, Kubernetes, and cloud ecosystems to inform platform evolution and roadmap development.
• Communicate complex graph and infrastructure concepts clearly to business and technical stakeholders.
• Champion experimentation and innovation in graph analytics and distributed systems engineering.
• Support strategic initiatives, embedding graph platforms into enterprise digital and AI transformation programmes.

People Specification

Essential Qualifications - NQF Level

BSc Computer Science, Engineering, Mathematics, Statistics, or related STEM field.

Preferred Qualification

Master Degree in Computer Science, Engineering, Mathematics, Statistics, or related STEM field.

Preferred Certifications

• TigerGraph certification, Kubernetes (CKA/CKAD), and cloud platform certifications (Azure preferred).
• Type of Exposure
• Graph engineering and large-scale graph platform deployment
• AKS Kubernetes cluster design and operations
• Distributed systems and cloud-native architecture
• Financial crime and fraud analytics using

Real-time and streaming data processing

• Enterprise integration and API-driven architectures
• DevOps, CI/CD, and infrastructure automation
• Strategy formulation and stakeholder engagement
• Minimum Experience Level
• 7+ year’s experience for Senior