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Airwallex is an AI-native financial operating system serving over 675,000 businesses globally, including McLaren Racing, Qantas, SHEIN, and TikTok. The company provides regulated financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific, with co-headquarters in San Francisco and Singapore and 2,300+ employees across 27 offices.
In this Staff Data Engineer role, you will own the data foundations powering Airwallex's Customer Data Platform, enabling teams to transform customer information into trusted, reusable data for analytics, machine learning, operational decision-making, and AI applications.
Key responsibilities include:
- Designing and owning scalable ETL pipelines across batch and real-time workflows using Databricks, DBT, and Spark
- Building reliable data foundations across data warehouses, data consumption platforms, and modern cloud data infrastructure
- Developing data models and data products supporting operational needs, agentic workflows, machine learning, and business intelligence, including star, snowflake, normalized, and denormalized designs
- Applying data engineering and AI best practices to solve practical problems in creative and scalable ways
- Partnering with globally distributed teams to deliver complex technical work with strong problem-solving, attention to detail, communication, and collaboration
This is a full-time, in-office role based in Singapore, requiring five days per week in the office.
REQUIREMENTS:
Essentials:
- Bachelor's degree or higher in Computer Science, Information Systems, Mathematics, or related field
- Minimum 7 years of experience designing and implementing scalable ETL pipelines, including batch and streaming workflows
- Experience with streaming technologies such as Apache Kafka or Apache Flink
- Strong proficiency in SQL, database management systems, data warehousing, and data modeling for business intelligence, machine learning, and operational needs
- Solid understanding of data schemas, including star, snowflake, normalized, and denormalized designs
- Excellent analytical and problem-solving abilities, attention to detail, and effective communication and collaboration skills
- Understanding of AI and interest in applying data engineering and AI in practical and creative ways
Preferred:
- Familiarity with Google Cloud Platform and modern data infrastructure tools, including Databricks and Airflow
- Experience working with globally distributed teams
