VP/AVP, Cloud and Data Engineer, Data Technology, Technology & Operations
DBS Bank
- Singapore
- Permanent
- Full-time
- Design and implement key components for highly scalable, distributed data collection and analysis system built for handling petabytes of data in the cloud.
- Work with architects of the analytics system and help in adopting best practices in backend infrastructure and distributed computing, that supports Machine Learning and GenerativeAI workloads.
- Implement core practice of Agile, leveraging cloud-native architecture patterns and using Test Driven Development, continuous integration/continuous delivery
- Continuously discover, evaluate and implement new cloud technologies to maximize analytical system performance
- Experience in one or more areas of big data, cloud and/or cloud-native application development
- Enterprise experience building complex solutions within AWS and experience with architecting AWS production workloads for Business and IT operations, across a hybrid cloud environment.
- Experience in Infrastructure and Infrastructure as Code (IaaC) is a must.
- Demonstrable strong cloud architecture or development experience, specifically Amazon Web Services (AWS) and/or Google Cloud Platform (GCP) with associate or specialist level certification.
- Hands-on experience with containers and containers orchestrators (kubernetes, openshift)
- Experience with Spark and different schema formats (Avro, Parquet, Carbondata)
- Development experience in Java/Python and pride in producing clean, maintainable code.
- Experience using high-throughput, distributed message queueing systems such as Kafka.
- Familiarity with tracing/observability solutions, e.g. OpenTelemetry, Zipkin
- Mastery of key development tools such as GIT, and familiarity with collaboration tools such as Jira and Confluence or similar tools.
- Experience with distributed databases, such as Cassandra, and the key issues affecting their performance and reliability.
- Experience with SQL engines (e.g. MySQL, PostgreSQL)
- The ability to work with loosely defined requirements, and exercise your analytical skills to clarify questions, share your approach and build/test elegant solutions in weekly sprint/release cycles.