Data Engineering Manager

About this role

ABOUT AIRWALLEX

Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.

Proudly founded in Melbourne, we have a team of over 2,200 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.

ATTRIBUTES WE VALUE

We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you’re motivated by our mission and operating principles https://www.airwallex.com/us/operating-principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor.

You're humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end-to-end. You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let’s build what’s next.

ABOUT THE TEAM

The Knowledge Platform team is at the heart of our company's data and AI strategy. We are building the foundational infrastructure that empowers the entire company to leverage data, AI, and ML into business impact. We accomplish this by creating platforms that handle the entire data and AI/ML lifecycle, simplifying the interface while providing proper safety and governance. This includes managing our data infrastructure (Databricks, Spark, Kafka, etc.), the technology to serve that data to our users (RAG, MCP, etc.), and the platform to host and govern these AI/ML models.

In 2026, our team’s overarching mission is to evolve our full data ecosystem—encompassing both platform and models—into a fully AI agent-ready infrastructure; we will empower customers to engage directly with the data platform to extract actionable value through capabilities like analytics and natural language querying, while also upgrading the platform to deliver robust, real-time performance for instant, data-driven decision-making.

WHAT YOU'LL DO

We’re looking for a Data Engineering Manager to lead a team within Knowledge Platform and help scale the data foundations that power Airwallex’s products, analytics, and operational decision-making. In this role, you will lead engineers working on data modeling, pipelines, and analytics-ready datasets across domains such as regulatory reporting, data content foundation, customer and business data, and growth data. You’ll partner closely with engineering leaders, product and business stakeholders, and adjacent platform teams to turn ambiguous business needs into reliable, well-structured data solutions.

This role is based in Singapore.

RESPONSIBILITIES

- Lead, coach, and grow a team of Data Engineers, setting a high bar for technical quality, execution, and ownership.

- Define the technical direction for your team across data modeling, pipeline architecture, data quality, observability, and lifecycle management.

- Partner with leaders across engineering, product, analytics, risk, and operations to prioritise the most important data problems and translate them into scalable solutions.

- Drive the design and delivery of reliable batch and near real-time data pipelines that support critical internal and product-facing use cases.

- Improve engineering standards across SQL, dbt, Spark, Airflow, and Databricks, including performance, maintainability, testing, documentation, and governance.

- Contribute to org-wide planning and cross-team execution, especially where Data Engineering interfaces with Data Platform, AI enablement, and broader Knowledge Platform priorities.

WHO YOU ARE

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.

MINIMUM QUALIFICATIONS

- Bachelor’s degree or higher in Computer Science, Information Systems, Mathematics, or a related field.

- Minimum 8 years of experience in data engineering, with prior people management experience.

- Strong hands-on foundation in modern data engineering

- Experience designing and operating scalable data pipelines and datasets used by multiple downstream stakeholders or systems.

- Demonstrated ability to lead technical projects end to end, from problem definition and architecture through execution, rollout, and ongoing improvement.

- Strong communication skills and the ability to work effectively with technical and non-technical stakeholders across functions.

- A practical understanding of data quality, governance, reliability, and operational excellence in production environments.

PREFERRED QUALIFICATIONS

- Experience leading Data Engineering teams in a high-growth technology company or a similarly fast-paced environment.

- Background supporting complex business domains such as financial data, regulatory reporting, growth, customer data, or internal data products.

- Familiarity with Databricks-based data stacks and lakehouse-style architectures.

- Experience working closely with platform or infrastructure teams on shared standards, tooling, and developer workflows.

- Exposure to data governance, access control, lineage, or…