About Airwallex
Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 100,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.
Proudly founded in Melbourne, we have a team of over 1,500 of the brightest and most innovative people in tech located across more than 20 offices across the globe. Valued at US$5.6 billion and backed by world-leading investors including Sequoia, Lone Pine, Greenoaks, DST Global, Salesforce Ventures and Mastercard, Airwallex is leading the charge in building the global payments and financial platform of the future. If you’re ready to do the most ambitious work of your career, join us.
Who You Are? Role Overview:
In 2024, the Data Platform Engineering team is going to implement various data processing tasks on the newly built next-generation data platform. We aim to further optimize data storage, processing, application, interfaces, and other dimensions. Throughout the continuous iteration process, we will also incorporate new data components and consider new data architectures (such as Lake House) to achieve faster data scheduling, significantly reducing data latency and enabling more efficient operation of data engineering applications.
In this data engineering role, we are seeking engineers with a background in data engineering to join us in various aspects of data engineering, leveraging your past experiences in the field.
In this role, you will:
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Engage in technical decision-making, custom development, integration, and performance optimization at the foundational level, extending to the development of service layer infrastructure components, application layer, and data processing, including third-party data integration. Your contributions will enable Airwallex to evolve into a truly data-driven organization.
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Develop and automate large-scale, high-performance distributed data processing systems (batch/streaming) to drive Airwallex’s business growth and enhance product experiences.
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Advocate for high-quality software engineering practices to establish scalable data infrastructure and pipelines.
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Contribute to defining shared data engineering tool standards to enhance the productivity and output quality of data engineers across the company.
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Provide guidance to junior engineers.
You might be a great fit if you:
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Have 5+ years of relevant experience as a data engineer.
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Hold a Bachelor’s or Master’s degree in CS/CE/CIS, (or equivalent experience) with knowledge of Kotlin / Java / Scala / Python / SQL. Knowledge of Kafka, Data Lake, Spark, Flink, DBT, Spring Boot,, Hadoop, BigQuery, and Snowflake is preferred.
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Ability to take ownership of designing, building, and operating distributed systems and establishing overarching data architecture.
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Possess strong working knowledge of Real-time/Batch processing systems.
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Have experience with working data at PB scale.
Equal opportunity
Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don’t regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.
Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary.
