Senior Data Engineer, Knowledge Platform, Foundational Data

ABOUT 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 https://www.airwallex.com/en-us/operating-principles to see it in full.

HOW YOU'LL MAKE IMPACT

Knowledge Platform is building the data foundations that support critical business and AI use cases across Airwallex. You'll own reliable, scalable data solutions end to end while helping raise the bar for technical design and execution.

- Design and build scalable data pipelines and data models that power critical use cases across Knowledge Platform teams and business domains. - Partner closely with engineering and cross-functional stakeholders to turn ambiguous data needs into reliable, well-structured solutions that support decision-making and product development. - Own projects end to end, from system and pipeline design through performance, monitoring, and ongoing improvements in data quality and reliability. - Raise the bar on technical design and execution as a senior member of the team, bringing strong engineering judgment, practical problem-solving, and a high standard of ownership.

You'll work from our Singapore office five days a week.

WHAT WE'RE LOOKING FOR

ESSENTIALS

- Bachelor’s degree or higher in Computer Science, Computer Engineering or a related field. - At least five years of experience designing and implementing scalable ETL pipelines, across batch and real-time workflows, using technologies such as DBT and Spark - Strong proficiency in SQL, database management systems, data warehousing, and data modelling for business intelligence, machine learning, and operational needs. - Strong understanding of data schemas, including star, snowflake, normalised, and denormalised designs. - Familiarity with Google Cloud Platform and modern data infrastructure tools, including Databricks and Airflow. - Knowledge of data governance practices, the six key governance pillars, and regulatory requirements in the financial industry. - Strong problem-solving, attention to detail, communication, and collaboration skills, including experience working with globally distributed teams. - Understanding of AI and an interest in applying data engineering and AI in practical and creative ways.