Big Data Platform Architect – AI & Data Infrastructure Lead, Singapore

This is a hands-on technical leadership role at the heart of our Data & AI delivery practice. As a Big Data Platform Architect, you will be the backbone of enterprise-scale data platforms — ensuring the infrastructure that powers AI models, data pipelines, and analytics tools is stable, scalable, and production-ready.

You will work embedded within client engagements, owning the platform layer that everything else runs on — from AI/ML workloads to data visualisation. If you're the kind of engineer who takes pride in knowing that nothing falls over because of you, this role is built for you.

• Own the platform. Design, build, and maintain enterprise data infrastructure on Red Hat OpenShift — the foundation that tools like Cloud Pak for Data and H2O run on top of.
• Keep the lights on and scale up. Ensure platform stability, security, and performance as workloads and teams grow. When something breaks, you're the person who knows exactly why.
• Automate everything. Build and manage CI/CD pipelines via GitLab so that code changes, deployments, and configurations are tested and released reliably without manual intervention.
• Lead a technical team. Guide and support a team of engineers, making architectural decisions and setting standards for how the platform is built and operated.
• Bridge the gap. Translate complex infrastructure decisions into clear language for client stakeholders, project managers, and non-technical teams.
• Integrate and evolve. Onboard new tools and technologies into the platform ecosystem — including data virtualization, search, and visualization layers — as client needs grow.

• Strong hands-on experience with Red Hat OpenShift — administration, deployment, and troubleshooting at enterprise scale
• Solid working knowledge of RHEL (Red Enterprise Linux) — you understand what sits beneath the container layer
• Experience managing CI/CD pipelines (GitLab preferred) — you've built or maintained automated deployment workflows
• Ability to lead technical teams and communicate clearly with both engineers and business stakeholders
• Comfortable working in a client-facing consulting environment

• Experience with IBM Cloud Pak for Data or similar enterprise data platforms
• Familiarity with Tableau or other data visualisation tools
• Exposure to Denodo, ElasticSearch, or Quantexa
• Cloud infrastructure knowledge (AWS, Azure, or GCP)