Director, Knowledge Platform Engineering (relocate to Singapore)

Airwallex

1d

About The Position

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.
Airwallex has established dual HQs in San Francisco, CA, and Singapore, and recently crossed the US$1B ARR threshold. The business was proudly founded in Melbourne, and now, in our 10th year, we have a team of over 2,000 of the brightest and most innovative people in technology across 26 offices worldwide. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Activant, Lingotto, Robinhood Ventures, TIAA Ventures, Visa, Airtree, Blackbird, Sequoia, DST Global, Greenoaks, Salesforce Ventures, Lone Pine, and Square Peg, 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.
We’re hiring a Director, Knowledge Platform Engineering (based in Singapore) to own the architecture, delivery, and adoption of a governed, reusable Data → Knowledge → Skills stack that powers analytics, AI agents, and real-time decisioning across the company. This is a product-facing platform leadership role. The successful leader will design and scale the semantic and operational layers on top of our Data Lakehouse (Databricks), enforce strong governance and lineage, and productize capabilities so both human analysts and machine agents reason and act consistently.
Our platform is evolving beyond raw data storage into a structured, scalable system comprising three tightly integrated layers:
Data – Governed, well-modeled, structured datasets including transactional records, event streams, dimensional models, and feature tables. This foundation must deliver high quality, strong lineage, and built-in regional compliance. It should be clean, trusted, and fully queryable.
Knowledge – A semantic layer that makes data meaningful to both humans and machines. This includes standardized business metric definitions, entity relationships, contextual documentation, and company-specific domain knowledge. It enables analysts and AI agents alike to ask questions such as “What is our net revenue retention in SEA?” and receive consistent, trustworthy answers without having to reverse-engineer underlying schemas.
Skills – Operationalized capabilities that act on data and knowledge. These include reusable analytical workflows, agent-callable tools, automated pipelines, API endpoints, and transformation primitives. Together, they form the building blocks that allow AI agents and internal teams not only to query information but to reason, automate, and execute reliably.
We are looking for a leader who can architect and scale this governed stack across regions and use cases, while ensuring it remains accessible and intuitive for Data Science, AI engineering, and technical business stakeholders. The objective is to create a shared foundation that enables both human analysts and AI agents to reason consistently and act confidently.
A critical component of this role is ownership of the regional and global data localization strategy within our Databricks environment. This includes designing architectural patterns that satisfy regulatory requirements while preserving a unified global data model across priority markets. The platform must reconcile local compliance constraints with global consistency in definitions, metrics, and knowledge artifacts.
You will partner closely with Data Science, AI engineering, Product, and Risk teams to ensure the platform supports rapid experimentation, intelligent automation, and high-quality decision-making, transforming raw data into durable knowledge and deployable skills across the organization.

Requirements

• 15+ years in data or platform engineering, with 5+ years leading engineering teams in complex, multi-region environments.
• Proven experience architecting and scaling modern data platforms that extend beyond storage to include semantic layers, metadata systems, or knowledge graphs.
• Strong hands-on expertise in data modeling (transactional, event-driven, dimensional, feature tables) with robust data quality, lineage, and observability practices.
• Experience designing and operationalizing a governed semantic layer with standardized, auditable business metric definitions.
• Track record of building reusable, programmatic capabilities on top of data platforms (APIs, orchestration frameworks, analytical workflows, agent-callable tools).
• Deep familiarity with modern lakehouse architectures, particularly within a Databricks environment.
• Experience implementing regional data localization and residency strategies while maintaining a unified global data model.
• Strong understanding of data governance, privacy, and regulatory controls in multi-jurisdictional contexts.
• Platform-as-product mindset, with experience driving adoption, improving developer experience, and operating with clear SLAs/SLOs and measurable impact.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed