The posting, in Airwallex's own words
archived Oct 8, 2026About 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 2,300 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.
How you'll make impact
Our Strategic Data team builds the data foundations that support business intelligence, machine learning, and operational decision-making. You'll help create reliable, scalable data models and pipelines while improving how teams use data across the business. Design and implement robust, scalable data models that support business intelligence, machine learning, and operational needs. Select appropriate schema designs—including star schema, snowflake, normalized, and denormalized models—based on the use case. Partner with business teams to translate data needs into clean, structured, and well-documented models, while promoting a single source of truth across data layers and pipelines. Build and maintain batch and streaming ETL pipelines across the full data workflow, from ingestion and transformation through delivery. Maintain data consistency, traceability, and quality across multiple data sources and domains, including distributed or multi-datacenter environments where relevant. Contribute to data governance strategies, policies, and standards across areas such as data quality, stewardship, metadata, master data, privacy, security, and lifecycle management. Work with Data Platform Engineers and Product Managers to identify root causes of data issues and deliver efficient, scalable solutions. Explore practical ways for data engineering and AI to work together across our products and operations. This role is based in San Francisco or Seattle, and you'll be expected to work from the office three days a week.