9 days ago
Singapore, SingaporeStaff+
Responsibilities
- Own scalable ETL pipelines across batch and real-time workflows.
- Build reliable data foundations across warehouses, data consumption platforms, and modern cloud infrastructure.
- Develop data models and products using star, snowflake, normalized, and denormalized designs.
- Support operational needs, agentic workflows, machine learning, business intelligence, and practical AI applications.
- Apply data engineering and AI best practices to solve scalable technical problems.
- Partner with globally distributed teams to deliver complex technical work.
Requirements
- Bachelor’s degree or higher in Computer Science, Information Systems, Mathematics, or a related field.
- At least seven years of experience designing and implementing scalable ETL pipelines across 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.
- Understanding of star, snowflake, normalized, and denormalized data schemas.
- Strong analytical, problem-solving, communication, collaboration, and attention-to-detail skills.
- Understanding of AI and interest in applying data engineering and AI to practical problems.
- Familiarity with Google Cloud Platform, Databricks, and Airflow is preferred.
- Experience working with globally distributed teams is preferred.
Benefits
- This is an in-office role based in the Singapore office five days per week.
Tech Stack
Categories
Data Engineering
About Airwallex
Airwallex builds a global payments and financial operations platform for businesses, offering payment acceptance, multi-currency accounts, FX and transfers, card issuing, treasury and spend management via APIs and web apps. It monetizes through transaction and foreign-exchange fees and related account services. Founded in Melbourne in 2015 and privately held, the company serves customers worldwide, with notable users including Brex, Canva and Qantas.