Senior Data Engineer - AVP

About the role

As Singapore's longest established bank, we have been dedicated to enabling individuals and businesses to achieve their aspirations since 1932. How? By taking the time to truly understand people. From there, we provide support, services, solutions, and career paths that meet their individual needs and desires. Today, we're on a journey of transformation. Leveraging technology and creativity to become a future-ready learning organisation. But for all that change, our strategic ambition is consistently clear and bold, which is to be Asia's leading financial services partner for a sustainable future. We invite you to build the bank of the future. Innovate the way we deliver financial services. Work in friendly, supportive teams. Build lasting value in your community. Help people grow their assets, business, and investments. Take your learning as far as you can. Or simply enjoy a vibrant, future-ready career. Your Opportunity Starts Here. Senior Data Engineer We are seeking a highly skilled and motivated Senior Data Engineer with expertise in cloud-native data engineering on any major cloud platform. The ideal candidate will have hands-on experience with Spark, PySpark, Iceberg, streaming systems, and open data catalogue/governance frameworks . This role is suitable for individuals with minimum 3 years of relevant industry experience and have strong fundamentals, high learning agility, and a passion for building modern data systems.

Responsibilities

• Cloud-Native Data Engineering
• Design and build scalable, reliable data pipelines using native services provided by the chosen cloud platform.
• Implement data lakehouse solutions using Apache Iceberg and open, interoperable metadata/catalogue frameworks.
• Modernize existing data processing pipelines with cloud-first architectural principles.
• Streaming & Real-Time Processing
• Develop and maintain real-time streaming pipelines using the platform's native streaming, messaging, and event ingestion services.
• Build structured streaming logic using Spark Structured Streaming or equivalent cloud-native stream processing tools.
• Migration & Modernization
• Participate in the migration of complex SQL workloads and legacy processing systems into a cloud-native architecture.
• Optimize SQL and transformation logic to leverage cloud-scalable compute and storage.
• Data Engineering & Automation
• Build end-to-end ETL/ELT workflows using Python and Unix/Linux shell scripting .
• Write efficient SQL for complex data transformations and analytics.
• Develop automated data quality checks, validation processes, and operational monitoring.
• Data Governance & Catalogue
• Leverage open-source catalogue/governance solutions (e.g., Open Data Catalogue, OpenMetadata, DataHub ) to ensure lineage, metadata capture, and data accessibility.
• Support data governance practices across domains and teams.
• Collaboration & Delivery
• Work closely with analysts, data scientists, and stakeholders to deliver robust, scalable data solutions.
• Troubleshoot pipeline issues, ensure data reliability, and optimize processing performance.
• Continuously explore new technologies and best practices within the data engineering ecosystem.

Requirements

• A degree in Computer Science, Information Technology, or a related field
• At least 3 years of experience in software development, preferably in a banking or financial services environment
• Proficient in one or more programming languages, such as Java, Python, or C++
• Experience with Agile development methodologies and version control systems such as Git
• Strong problem-solving skills, with the ability to analyze complex technical issues and develop creative solutions
• Excellent communication an

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