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Airwallex is a unified payments and financial platform serving over 250,000 global businesses including Brex, Navan, Qantas, and SHEIN. The company operates across 27 offices worldwide with 2,300+ employees and is valued at $11 billion, backed by leading investors including T. Rowe Price, Visa, Mastercard, and Sequoia.
The Knowledge Platform team sits at the heart of Airwallex's data and AI strategy, building foundational infrastructure that enables the entire company to leverage data, AI, and ML for business impact. The team manages data infrastructure (Databricks, Spark, Kafka), data serving technology (RAG, MCP), and platforms for hosting and governing AI/ML models. In 2026, the team's mission is to evolve the full data ecosystem into AI agent-ready infrastructure, enabling customers to engage directly with the data platform for analytics and natural language querying while delivering robust real-time performance.
As Staff Engineer for the Data Platform, you will serve as a high-level architect overseeing the strategy, architecture, development, and operation of Airwallex's data and AI platforms. You will influence data-driven and AI-powered decision-making across the company and build a high-performing team in a fast-paced environment. Key responsibilities include identifying and resolving company-wide challenges using cutting-edge data platform solutions, providing visionary technical direction while solving complex problems hands-on, advocating for best practices and a culture of craftsmanship, and mentoring the data platform team on both technical and professional development.
You will work on company-wide initiatives, collaborate across diverse teams and stakeholders, balance execution velocity with research and scalable design, and provide technical leadership on significant projects covering ETL frameworks, metrics stores, infrastructure management, and data security. The role is based in Seattle.
REQUIREMENTS:
Minimum:
- 8+ years of experience in Data Platform or equivalent combination of work and academic exposure in a quantitative field
- Proven experience leading company-wide initiatives across multiple teams or influencing tech roadmap planning
- Effective collaboration with diverse teams and stakeholders to drive tangible business outcomes
- Demonstrated ability to balance execution and velocity with in-depth research, statistical understanding, and scalable design
- Track record of mentoring and investing in the development of scientists, engineers, and peers
- Technical leadership experience on significant projects covering ETL frameworks, metrics stores, infrastructure management, and data security
- Proficiency in building, deploying, and maintaining reliable multi-geographical data pipelines at scale
- Familiarity with workflow or orchestration frameworks such as Airflow, DBT, etc.
Preferred:
- Hands-on design experience in crafting data processing patterns for modern Lakehouse architecture
- Design and development experience with standard framework modules, high-performance services, and client libraries for big data using GCP, Databricks, BigQuery, DataProc, Kafka, Kubernetes, Spark, DataFlow, Google Cloud Storage, and Airflow
- Excellent written and verbal communication skills tailored for diverse audiences (leadership, users, company-wide)
- Ability to rapidly evaluate technologies and conduct proof of concepts to drive architecture design
- Experience thriving in complex environments
