VP/AVP, Cloud Engineer, Data Platform, Group Technology

Business Function Group Technology enables and empowers the bank with an efficient, nimble and resilient infrastructure through a strategic focus on productivity, quality & control, technology, people capability and innovation. In Group Technology, we manage the majority of the Bank's operational processes and inspire to delight our business partners through our multiple banking delivery channels.

Responsibilities

• You will partner with architects, data engineers, data scientists, security and governance teams to deliver scalable, secure and resilient platform capabilities for analytics, AI/ML, agentic and business-critical workloads.
• You will provide technical leadership, establish engineering standards and serve as an escalation point for complex production issues.
• Design, implement and operate scalable, resilient and cost-efficient data, analytics, AI and agentic platform capabilities on GCP.
• Build reusable infrastructure and deployment patterns that support the development, productionisation and operation of enterprise AI and agentic workloads, including agent frameworks and model-serving environments.
• Design secure and scalable integration patterns connecting AI agents with enterprise data sources, APIs, tools and business systems.
• Design and implement identity, access and governance controls for human and non-human identities, including service accounts, workload identity, federation and delegated access.
• Define least-privilege, policy-driven access patterns for AI services, enterprise data, APIs and platform resources.
• Lead technical design discussions, architecture reviews and engineering governance; define standards and operational controls for production workloads.
• Implement cloud-native engineering practices including Infrastructure as Code, CI/CD, automated testing and DevSecOps controls.
• Lead troubleshooting and remediation of complex production issues across cloud infrastructure, data platforms, Kubernetes and distributed systems; act as the L3 escalation point, lead root cause analysis and implement permanent corrective actions.
• Mentor engineers, conduct design and code reviews, promote engineering best practices and evaluate emerging cloud and AI technologies to improve platform capabilities.
• Requirements 8+ years of infrastructure, platform or cloud engineering experience, including at least 5 years working with GCP.

Preferred

• Google Professional Cloud Architect, Professional Cloud DevOps Engineer or Professional Data Engineer certification.
• Experience leading engineering squads or serving as technical lead for cloud initiatives.
• Development experience in Python and/or Java.
• Experience with Kafka and event-driven architectures.
• Experience with OpenTelemetry, Grafana or Prometheus.
• Experience with SQL platforms including PostgreSQL and MySQL.
• Experience supporting regulated enterprise or financial-services environments.

Responsibilities

As a Cloud Engineer (Data & AI Platform), you will be responsible for the design, engineering, security, reliability and operational excellence of enterprise-scale data, analytics, AI and agentic platforms on Google Cloud Platform (GCP).

Strong hands-on experience designing, implementing and operating enterprise-scale solutions on GCP, including production workloads in hybrid cloud environments. Experience engineering platforms that enable AI/ML, Generative AI or agentic workloads, including reusable platform services, deployment patterns or model-serving capabilities. Expertise in BigQuery, Dataproc, Cloud Storage and cloud-native data platforms, with strong knowledge of Spark and data formats such as Avro and Parquet. Hands-on experience with Kubernetes, Docker and containerised workloads in production environments. Hands-on experience with Terraform, Infrastructure as Code, CI/CD and cloud automation practices. Strong understanding of cloud IAM, service accounts, federated identities, workload identity, delegated authorisation and secure machine-to-machine or application-to-application access models. Experience implementing enterprise security controls, including least-privilege IAM, encryption, secrets and key management, policy-based access controls and workload-level security automation. Knowledge of data governance and secure data-access patterns, including fine-grained access controls and entitlement-aware authorisation.

Location

DBS Asia Hub Job: Technology Schedule: Regular Employee Status: Full time