Data Platform Principal Architect

Proudly founded in Melbourne, we have a team of over 2,300 of the brightest and most innovative people in tech across 27 offices around the globe. Valued at US$11 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and...

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 ...

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 tha...

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.
This role is based in Singapore.
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 experimentation and high-quality decision-making.
Lead global data modeling efforts, creating unified schemas that accommodate regional variance.
Define and implement “Agent Interfaces”—APIs and tools that enable AI agents to interact with Knowledge and Skills layers.
Implement Governance-as-Code, ensuring automated data lineage and quality controls are embedded directly into the data platform.

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.
 
10+ years of experience designing and building large-scale data systems with strong architectural fundamentals.
Hands-on experience with the Databricks ecosystem, including Unity Catalog and Delta Lake.
Experience implementing semantic layers or metric stores to enable consistent reporting and analytics.
Solid understanding of how AI/agent-based systems consume data, with experience building APIs or data services to support them.
Experience designing data solutions that meet regional data residency and compliance requirements.
Demonstrated senior-level individual contributor experience, including leading design reviews and mentoring engineers.
NA
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