Senior Data Platform Engineer, Knowledge Platform & AI Enablement

About the role

Airwallex, the AI-native financial operating system used by more than 675,000 businesses, is hiring a Senior Data Platform Engineer in its Singapore office. The Data Platform Engineering team builds on a next-generation data platform, optimizing storage, processing, application and interfaces, and incorporating new architectures such as Lake House to reduce data latency. The Knowledge Platform team turns structured and unstructured information into trusted context for people and AI systems.

Key responsibilities

• Help build the next generation of Airwallex's data and knowledge infrastructure.
• Own the design, development and operation of large-scale distributed data systems across batch and streaming workloads.
• Drive technical decisions across data processing, service-layer infrastructure, application-layer systems, third-party integrations and performance optimisation.
• Build and automate high-performance distributed data processing systems supporting data and AI capabilities.
• Lead medium- and large-scale engineering projects from system design through delivery.
• Raise engineering standards through scalable data architecture, shared tooling, high-quality software practices and technical guidance for other engineers.

Required profile

• 5+ years of relevant experience as a data engineer.
• Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems or equivalent experience.
• Experience designing, building and operating distributed systems and making technical decisions across data processing, infrastructure, integrations and performance.
• Experience developing and automating large-scale distributed data processing systems, and mentoring or guiding other engineers.
• Preferred: experience in a high-growth or scaling environment, and owning the roadmap yourself.

Required skills

• Strong programming in Kotlin, Java, Scala, Python and SQL.
• Strong working knowledge of real-time and batch data processing systems.
• Experience with data at petabyte scale.
• Preferred: Kafka, data lakes, Spark, Flink, dbt, Spring Boot, Hadoop, BigQuery or Snowflake; lakehouse architectures; shared data engineering standards and tools.

The role is based in the Singapore office five days a week, with collaboration across multiple countries and time zones.