SVP, Senior Cloud Engineer (Data & AI Platform), Group Technology (WD87133)

DBS Bank Limited; Singapore; On-site; SGD 170,000 - 260,000; Full time

Job summary

DBS Bank Limited in Singapore invites a Senior Cloud Engineer (Data & AI Platform) to design, engineer, and operate enterprise-scale data and analytics platforms on Google Cloud. You will partner with architects, data scientists, and platform teams to deliver secure, scalable cloud solutions supporting AI/ML workloads and business-critical tasks.

You will guide engineering best practices, mentor juniors, and drive RCA and permanent fixes while advancing observability, reliability, and cost

Qualifications

• 10+ years of infra or cloud engineering with 5+ years in GCP.
• Hands-on with Kubernetes, Docker in production.
• Experience enabling AI/ML or Gen AI workloads.
• Strong Spark, BigQuery, Dataproc and data platforms knowledge.
• Terraform and IaC expertise.

Responsibilities

• Design and support enterprise AI/data platforms on GCP.
• Lead architecture reviews and governance discussions.
• Design, implement and operate scalable data platforms on GCP.
• Mentor junior engineers and conduct design/code reviews.
• Lead incident RCA and remediation efforts.
• Drive observability and reliability improvements via SRE practices.

Skills

GCP

Kubernetes

Terraform

Docker

BigQuery

Dataproc

Spark

CI/CD

AI/ML platforms

Tools

OpenTelemetry

Grafana

Prometheus

PostgreSQL

MySQL

Kafka

Job description

Business Function

Group Technology enables and empowers the bank with an efficient,nimbleand resilient infrastructure through a strategic focus on productivity, quality & control, technology,peoplecapability and innovation. In Group Technology, we managethe majority ofthe Bank's operational processes andinspire to delightour business partners through our multiple banking delivery channels.

Job Responsibilities

As a Senior Cloud Engineer(Data & AI platform), you willbe responsible forthe design, engineering, reliability and operational excellence of enterprise-scale data,analyticsand agentic aiplatforms running on Google Cloud Platform (GCP). You will partner with architects, data engineers, datascientistsand platform teams to deliver scalable,secureand resilient cloud solutions supportingagentic,analytics, AI/MLand business-critical workloads. You will provide technical leadership, drive engineering bestpracticesand serve as an escalation point for complex production issues.

• Design and support infrastructure capabilities enabling enterprise agentic frameworks and AI agent deployment patterns.

• Design, implement andoperatehighly scalableand resilientdata and analytics platforms on GCP handling large-scale workloads.

• Analysebusiness and technical requirements and translate them into secure,resilientand cost-efficient solution designs.

• Lead technical design discussions and contribute to architecture reviews and engineering governance activities.

• Design,engineerandoperatecloud infrastructure supporting AI/ML and Generative AI workloads.

• Support enterprise adoption of AI platforms, model serving environments and agentic application architectures.

• Implement cloud-native engineering practices includingInfrastructure asCode, CI/CD, automatedtestingandDevSecOpscontrols.

• Lead troubleshooting and remediation of complex production issues across infrastructure, data platforms,Kubernetesand distributed systems.

• Act as L3 escalation point for major incidents, drive root causeanalysisand implement permanent corrective actions.

• Drive observability,monitoringand reliability improvements through SRE principles,automationand proactive capacity management.

• Optimiseperformance,scalabilityand cost acrossBigQuery,Dataproc, Spark and related cloud services.

• Mentor junior engineers, conduct design/code reviews and promote engineering best practices.

• Continuously evaluate and adopt emerging cloud technologies to improve platform capabilities.

Job Requirements

• 10+ years of infrastructure,platformor cloud engineering experience with at least 5 years in GCP.

• Experience supporting or engineering platforms that enable AI/ML, Generative AI or Agentic workloads will be highly advantageous.

• Strong hands-on experience designing,implementingandoperatingenterprise-scale solutions on GCP.

• DeepexpertiseinBigQuery,Dataproc, Cloud Storage and cloud-native data platforms.

• Hands-on experience with Kubernetes,Dockerandcontainerisedworkloads in production environments.

• Strongproficiencyin Terraform and Infrastructure as Code practices.

• Experience architecting and supporting production workloads across hybrid cloud environments.

• Strong knowledge of Spark and schema formats such as Avro and Parquet.

• Demonstratedexperiencetroubleshooting complex distributed stems and cloud-native workloads.

• Experience leading root cause analysis, problemmanagementand operational improvement initiatives.

• Hands-on experience with infrastructure monitoring, observability, loganalysisand incident response.

• Ability to implement and automate workload-level security controls withinGCP.

• Strong stakeholder management,communicationand technical leadership skills.

• Experience working within Agile delivery environments.

Nice to Have

• Google Professional Cloud Architect, Professional Cloud DevOpsEngineeror Professional Data Engineer certification.

• Experience leading engineering squads or serving astechnicallead for cloud initiatives.

• Development experience in Python and/or Java.

• Experience with Kafka and event-drivenarchitectures.

• Experience withOpenTelemetry,Grafanaor Prometheus.

• Experience with SQL platforms including PostgreSQL and MySQL.

• Experience supporting regulated enterprise orfinancial-servicesenvironments.