Enterprise Architect – Data, AI & Platforms

About the role

The Enterprise Architect – Data, AI & Platforms is a senior leader responsible for shaping the end‑to‑end technology architecture that powers data‑driven decision making, intelligent automation, and digital transformation across the enterprise.

Key responsibilities

• Define and maintain target architecture for data, AI, platforms and infrastructure, including principles, standards and reference models.
• Establish guardrails that ensure data quality, AI readiness, platform automation, integration, standardisation and security by design.
• Lead design of data lakes, data warehouses, real‑time streaming, ML platforms and model‑lifecycle management.
• Drive cloud, hybrid and on‑prem modernisation to support advanced analytics and AI workloads.
• Architect solutions for large‑scale analytics, ML training/inference, model deployment and intelligent automation.
• Oversee platform lifecycles such as virtualization, container platforms (OpenShift/Kubernetes), cloud services, storage and enterprise databases.
• Guide selection of infrastructure and cloud technologies that enable AI acceleration and distributed computing.
• Partner with business and technology stakeholders to translate outcomes into scalable, future‑proof architectures.
• Provide technical leadership, mentorship and conduct cross‑functional architecture reviews.

Required profile

• Senior‑level experience in enterprise architecture, data engineering or AI/ML platform design.
• Proven ability to create and govern architecture roadmaps across complex, multi‑cloud environments.
• Strong understanding of regulatory compliance for data governance, security and privacy.
• Excellent communication skills to influence both technical and business audiences.

Required skills

• Data Lakes and Data Warehouses
• Real‑time Streaming
• Machine Learning Platforms and Model Lifecycle Management
• Cloud Architecture (public, hybrid, on‑prem)
• Virtualisation and Container Platforms (OpenShift, Kubernetes)
• Enterprise Databases and Storage Solutions
• AI Acceleration and Distributed Computing
• DevOps, MLOps, DataOps, Observability and Automation
• Cybersecurity and compliance frameworks