Principal Architect, Data Knowledge Platform

About the 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 . 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. Principal Architect, Data Knowledge Platform Hiring Location: San Francisco Team Introductions: 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. Who You Are? Role Overview: We are looking for a Principal Architect who operates at the intersection of platform architecture, customer-facing data products, and AI enablement. This is not a traditional infrastructure role. Your mandate is to architect the governed, reusable data, knowledge, and skill layer that powers analytics, AI agents, and real-time decision systems across the business. As the most senior individual contributor on the team, you will be the primary technical authority responsible for evolving our platform beyond raw data storage into a structured system of three layers: Data Layer: You will design the patterns for governed, well-modeled structured datasets-from transactional records and event streams to dimensional models and feature tables. You will ensure high quality, strong lineage, and regional compliance are "baked in" to the foundation, keeping it clean, trusted, and queryable. Knowledge Layer: You will architect the semantic layer that makes data meaningful to both humans and machines. This includes business metric definitions, entity relationships, and contextual documentation. Your goal is to ensure an analyst or an AI agent can ask "what is our net revenue retention in SEA?" and receive a consistent, trustworthy answer without ever having to reverse-engineer a schema. Skills Layer: You will define the architecture for operationalized capabilities that act on data and knowledge. This includes reusable analytical workflows, agent-callable tools, automated pipelines, and transformation primitives. These are the building blocks that allow AI agents and internal teams to reason and act reliably, rather than just querying data. Responsibilities： Own the technical execution of regional and global data localisation strategies within the Databricks environment. Design scalable patterns that satisfy strict regulatory requirements while maintaining a unified global data model across priority markets. Reconcile local compliance constraints with global consistency in definitions, metrics, and knowledge artifacts. Partner with Data Science, AI Engineering, Product, and Risk teams to ensure the platform supports exp