Aaron Wang
Director (Head Of R&D Department) at OneConnect Financial Technology
Hangzhou City, Zhejiang, China
Summary
🤩
Rockstar🎓
Top SchoolAaron Wang is a seasoned technology leader and Director heading R&D for OneConnect Financial Technology, with over 15 years of hands-on experience and six years in senior leadership roles. He leads a 100+ person mixed team across product, dev, mobile, and QA for credit and lending services, blending product ownership with delivery and operational oversight. His background as a senior QAD at Baidu and QA lead across gaming and enterprise firms gives him deep expertise in automation, CI, performance testing, and large-scale system reliability. Aaron remains an active backend contributor to notable open-source projects like Apache DolphinScheduler, where he improved Yarn job tracing via AOP and added queue support—demonstrating practical depth in data orchestration. Based in Hangzhou and an Arsenal loyal, he combines rigorous academic training from Fudan University with a pragmatic engineering mindset that favors observable, production-safe changes.
6 years of coding experience
8 years of employment as a software developer
Master, Software Engineering, Master, Software Engineering at Fudan University
English
Github Skills (10)
javas10
sched10
java10
yarnpkg10
scheduler10
aspect-oriented-programming9
aop9
orchestration8
workflow-engine8
job-scheduling8
Programming languages (6)
Github contributions (5)
apache/dolphinscheduler
Oct 2022 - Jan 2023
Apache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow with low-code
Role in this project:
Back-end Developer
Back-end DeveloperContributions:353 reviews, 11 commits, 89 PRs in 2 months
Contributions summary:Aaron primarily contributed to the Apache DolphinScheduler project by improving the system's ability to collect application IDs for Yarn jobs, including the introduction of an AOP (Aspect-Oriented Programming) way to collect application IDs. This involved adding new modules, user properties, and environment configurations for Yarn tasks. Additionally, the user fixed a typo in the AOP code. Further contributions include addressing a bug related to duplicated keys when there are out parameters with the same names, and implementing the support for the queue definition for Yarn tasks.
dependenciesuser-interfacepipelineorchestrationdata-workflow
Radeity/dolphinscheduler
Jul 2022 - Nov 2023
Apache DolphinScheduler is a distributed and extensible workflow scheduler platform with powerful DAG visual interfaces, dedicated to solving complex job dependencies in the data pipeline and providing various types of jobs available out of box.
Contributions:196 pushes, 92 branches in 1 year 3 months
dependenciesdagschedulerjobpipeline
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