Staff Software Engineer, Data Platform

About the team

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.

What you'll do

As a high level architect (staff engineer), you will oversee the strategy, architecture, development, and operation of Airwallex's data and AI platforms. You will play a pivotal role in influencing data-driven and AI-powered decision-making processes. A key aspect of your role will also include building a high-performing team that excels in a fast-paced environment. Your leadership will be critical in mentoring the team, promoting a culture of innovation, and driving technical excellence.

Responsibilities:

• Spearheaded the identification and resolution of Airwallex-wide challenges using cutting-edge data platform solutions.
• Provide visionary technical direction, fostering a community within Airwallex's data realm, and actively leading in solving complex problems hands-on.
• Advocate for best practices across the data platform, instilling a culture of craftsmanship and innovation.
• Mentor the data platform team, nurturing both technical and professional development.

Who you are

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.

Minimum Requirements:

• A minimum of 8 years of experience in Data Platform or an 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.
• Experience providing technical leadership 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 Qualifications:

• Hands-on design experience in crafting data processing patterns for a modern Lakehouse architecture.
• Contribute to the design and development of standard framework modules, high-performance services, and client libraries for big data using tools like 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 various technologies and conduct proof of concepts to drive architecture design.
• Experience thriving in a complex environment