DBS Bank's Group Technology is hiring a VP-level Data Engineer in Singapore to build and run the bank's enterprise data platform — designing scalable data ingestion, transformation, and orchestration services using Apache Spark, Kafka, Spring Boot, Java/Python, Kubernetes, and data-lake tech like Iceberg and S3, with CI/CD pipelines and GenAI integration.
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.
Key Responsibilities
Design, develop, and implement scalable, distributed, and high-performance data services for data ingestion, transformation, computation, and orchestration.
Build and maintain enterprise-grade Big Data applications using Apache Spark (Batch & Streaming), Spring Boot, and Kafka.
Develop cloud-native and on-premises solutions leveraging Kubernetes (K8S) platforms for containerized deployments and workload orchestration.
Design and implement robust microservices and RESTful APIs using Java and Python.
Develop and optimize Spark jobs to ensure high performance, scalability, reliability, and efficient resource utilization.
Establish and enforce best practices, coding standards, and performance tuning guidelines for Apache Spark applications.
Translate functional and non-functional requirements into scalable technical solutions.
Work with modern data lake technologies, including Apache Iceberg and S3-based storage, to support enterprise data platforms.
Collaborate with cross-functional and cross-regional teams to deliver strategic data engineering initiatives.
Implement and support CI/CD pipelines using tools such as Jenkins, Git, and Bitbucket.
Ensure operational stability, production support readiness, monitoring, and continuous improvement of data platform services.
Drive innovation through the adoption of Generative AI technologies, integrating GenAI capabilities into applications and developing AI-powered agents where appropriate.
Actively participate in Agile delivery practices and contribute to engineering excellence across the organization.
Job Requirements
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline.
Minimum 8 years of experience in developing, maintaining, and supporting enterprise-class Big Data applications and Spring Boot services, preferably within the banking or financial services industry.
Strong hands-on experience with Apache Spark (Batch & Streaming), Apache Iceberg, YARN, Kubernetes (K8S) / Unikorn, Kafka, Spring Boot
Strong programming skills in Java and Python.
Experience designing and implementing Microservices Architecture and RESTful services.
Solid experience in Spark application development, troubleshooting, and performance tuning.
Good understanding of relational databases and SQL.
Hands-on experience with S3 and enterprise data lake architectures.
Experience with CI/CD tools such as Jenkins, Git, and Bitbucket.
Knowledge of containerization technologies and Kubernetes-based deployments.
Experience working in Agile development environments.
Strong analytical, problem-solving, and communication skills.
Ability to work proactively, independently, and effectively with cross-functional and cross-regional teams.
Experience integrating Generative AI capabilities into applications and developing intelligent agents is highly desirable.
Exposure to cloud-native architectures and distributed computing platforms is a plus.
Location:
DBS Asia Hub
Job:
Analytics
Schedule:
Regular
Employee Status:
Full time