Senior Data Platform Engineer, Knowledge Platform & AI Enablement

Airwallex; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Airwallex is seeking an experienced Data Engineer to join the Data Platform Engineering team in Singapore. You will design and operate large-scale distributed data systems, improving latency and reliability while shaping data architecture across the platform.

You’ll collaborate with teams to advance data and AI capabilities and support operational excellence. Requirements include 5+ years in data engineering, strong programming in Kotlin/Java/Scala/Python/SQL, and hands-on experience with

Qualifications

• Bachelor’s or Master’s in CS/CE/IS or equivalent.
• 5+ years of data engineering and distributed systems experience.
• Strong in real-time and batch data processing, scalable architectures.

Responsibilities

• Own design, development, and operation of large-scale data systems.
• Drive architectural decisions across data processing and infra.
• Build high-performance distributed data processing pipelines.
• Lead medium- to large-scale projects from design to delivery.
• Raise standards with scalable data infrastructure and tooling.

Skills

Data engineering

Distributed systems

Mentoring

Roadmap ownership

Education

CS/CE/IS degree

Tools

Kafka

Spark

Flink

dbt

Spring Boot

Hadoop

BigQuery

Snowflake

Job description

About Airwallex

Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.

We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.

We're co-headquartered in San Francisco and Singapore, with more than 2,700 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

About The Team

The Data Platform Engineering team is going to implement various data processing tasks on the newly built next-generation data platform. We aim to further optimize data storage, processing, application, interfaces, and other dimensions. Throughout the continuous iteration process, we will also incorporate new data components and consider new data architectures (such as Lake House) to achieve faster data scheduling, significantly reducing data latency and enabling more efficient operation of data engineering applications.

How you'll make impact

You’ll help build the next generation of Airwallex’s data and knowledge infrastructure, turning structured and unstructured information into trusted context for people and AI systems.

• Own the design, development, and operation of large-scale distributed data systems across batch and streaming workloads, improving data latency, reliability, and engineering productivity.
• Drive foundational technical decisions across data processing, service-layer infrastructure, application-layer systems, third-party data integrations, and performance optimisation.
• Build and automate high-performance distributed data processing systems that support Airwallex’s data and AI capabilities.
• Lead medium- and large-scale engineering projects from system design through delivery, creating impact across the team and wider organisation.
• Raise engineering standards through scalable data architecture, shared tooling, high-quality software practices, and technical guidance for other engineers.

You’ll work from our Singapore office five days a week.

What we're looking for

Essentials

• 5+ years of relevant experience as a data engineer.
• A Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Information Systems, or equivalent experience.
• Strong programming skills in one or more of Kotlin, Java, Scala, Python, and SQL.
• Experience designing, building, and operating distributed systems, including establishing overarching data architecture.
• Strong working knowledge of real-time and batch data processing systems.
• Experience working with data at petabyte scale.
• Experience making technical decisions across data processing, service-layer infrastructure, application-layer systems, third-party data integrations, and performance optimisation.
• Experience developing and automating large-scale, high-performance distributed data processing systems.
• A track record of driving medium- and large-scale engineering projects from design through delivery.
• A commitment to high-quality software engineering practices and scalable data infrastructure.
• Experience mentoring or providing technical guidance to other engineers.

Preferred

• Experience with Kafka, data lakes, Spark, Flink, dbt, Spring Boot, Hadoop, BigQuery, or Snowflake.
• Experience contributing to shared data engineering standards, tools, or platforms that improve engineering productivity and output quality.
• Experience with next-generation data architectures such as lakehouse systems.
• Experience working in a high-growth or scaling environment.

You’ll thrive here if

• You're comfortable owning the roadmap yourself.
• You own the outcome and you don't wait for permission to fix what's broken.
• You're comfortable with ambiguity. Give you a problem, not a prescription, and you'll run with it.
• You hold yourself to a high standard even when no one is watching. Quality and accountability aren't external expectations, they're internal ones.
• You value in-person collaboration and are happy being in the office five days a week.
• You enjoy working closely with people across multiple countries and time zones as part of one connected, global team, including flexing your hours occasionally to make that connection work.

Learn more about your team

The Knowledge Platform sits at the foundation of Airwallex’s Data and AI strategy. We are evolving traditional data infrastructure into knowledge infrastructure—turning structured and unstructured information into trusted, reusable context that helps people and AI systems make better decisions and take action.

You’ll build the platform end to end, from core technologies such as Databricks, Clickhouse, Spark, and Kafka to real-time analytics, knowledge retrieval and indexing, model infrastructure, agent capabilities, and AI interaction history. You’ll also develop the evaluation, annotation, feedback, governance, permission, and freshness frameworks required to operate AI reliably at global financial scale.

Our mission is making this ecosystem truly agent-ready. That means enabling teams to explore data through natural language, investigate business drivers in real time, and give AI systems secure access to the context and capabilities they need to support decisions and execute workflows.

If you want to build the foundation that turns Airwallex’s data into knowledge, knowledge into intelligence, and intelligence into measurable business impact, this is where that work happens.

Equal opportunity

Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.