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.
Job Responsibilities
As a Senior Cloud Engineer (Data & AI platform), you will be responsible for the design, engineering, reliability and operational excellence of enterprise-scale data, analytics and agentic ai platforms running on Google Cloud Platform (GCP). You will partner with architects, data engineers, data scientists and platform teams to deliver scalable, secure and resilient cloud solutions supporting agentic, analytics, AI/ML and business-critical workloads. You will provide technical leadership, drive engineering best practices and 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 and operate highly scalable and resilient data and analytics platforms on GCP handling large-scale workloads.
Analyse business and technical requirements and translate them into secure, resilient and cost-efficient solution designs.
Lead technical design discussions and contribute to architecture reviews and engineering governance activities.
Design, engineer and operate cloud 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 including Infrastructure as Code, CI/CD, automated testing and DevSecOps controls.
Lead troubleshooting and remediation of complex production issues across infrastructure, data platforms, Kubernetes and distributed systems.
Act as L3 escalation point for major incidents, drive root cause analysis and implement permanent corrective actions.
Drive observability, monitoring and reliability improvements through SRE principles, automation and proactive capacity management.
Optimise performance, scalability and cost across BigQuery, 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, platform or 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, implementing and operating enterprise-scale solutions on GCP.
Deep expertise in BigQuery, Dataproc, Cloud Storage and cloud-native data platforms.
Hands-on experience with Kubernetes, Docker and containerised workloads in production environments.
Strong proficiency in 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.
Demonstrated experience troubleshooting complex distributed stems and cloud-native workloads.
Experience leading root cause analysis, problem management and operational improvement initiatives.
Hands-on experience with infrastructure monitoring, observability, log analysis and incident response.
Ability to implement and automate workload-level security controls within GCP.
Strong stakeholder management, communication and technical leadership skills.
Experience working within Agile delivery environments.
Nice to Have
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.
Location:
DBS Asia HubJob:
TechnologySchedule:
RegularEmployee Status:
Full timeSkills Required
- 10+ years of infrastructure, platform or cloud engineering experience with at least 5 years in GCP.
- Hands-on experience designing, implementing and operating enterprise-scale solutions on GCP.
- Deep expertise in BigQuery, Dataproc and Cloud Storage.
- Hands-on experience with Kubernetes, Docker and containerised workloads in production.
- Strong proficiency in 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.
- Demonstrated experience troubleshooting complex distributed systems and cloud-native workloads.
- Experience leading root cause analysis, problem management and operational improvement initiatives.
- Hands-on experience with infrastructure monitoring, observability, log analysis and incident response.
- Ability to implement and automate workload-level security controls within GCP.
- Strong stakeholder management, communication and technical leadership skills.
- Experience working within Agile delivery environments.
What We Do
DBS Bank is a leading financial services group in Asia, headquartered in Singapore. It provides a full range of consumer, SME, and corporate banking services. The bank is recognized for its digital innovation, having been named 'World's Best Digital Bank' and 'World's Best Bank' by various publications. It also operates the DBS Foundation, which supports social enterprises and community initiatives, reflecting its commitment to creating impact beyond traditional banking.
