Staff Software Engineer, Data Platform

About the role

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. 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.

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.

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).
• Rapidly evaluate various technologies and conduct proof of concepts to drive architecture design.
• Experience thriving in a complex environment.