Xinghong Fang
Software Engineer at Optiver
Shanghai, Shanghai, China
Summary
👤
Senior🎓
Top SchoolXinghong Fang is a platform-focused software engineer with 14 years of experience building and operating production-grade infrastructure across finance and analytics firms, now at Optiver. He has led cross-functional teams as a Platform Engineering Lead and Principal Architect, specializing in SRE/DevOps and Kubernetes (CKA, CKAD, CKS) to deliver resilient, scalable platforms. His background spans research-driven quantitative shops (Winton, Man Group) to AI-focused consulting (QuantumBlack/McKinsey), giving him a rare blend of quantitative rigour and production engineering discipline. An active open-source contributor, he improved Athena integration and multi-account Kinesis support in the popular StreamAlert project, bridging data processing with Terraform-managed infra. He holds an MPhil in Advanced Computer Science from Cambridge and is based in Shanghai, bringing both deep technical mastery and practical platform operations experience.
14 years of coding experience
13 years of employment as a software developer
BSc, Computer Science, BSc, Computer Science at University of NottinghamMPhil, Advanced Computer Science, MPhil, Advanced Computer Science at University of Cambridge
Chinese, English
Github Skills (14)
terraformer10
amazon-kinesis10
aws10
kin10
python10
terraform10
athena9
serverless9
rule8
analyse8
testing8
rule-engine8
configuration-management7
cicd6
Programming languages (13)
Github contributions (5)
airbnb/streamalert
Jan 2018 - Jan 2018
StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using datasources and alerting logic you define.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:13 commits, 2 PRs, 14 comments in 10 days
Contributions summary:Xinghong contributed significantly to the project's Athena integration, adding recursive schema support and refactoring related helper functions. They also addressed linting issues, ensuring code quality. Moreover, the user implemented and tested improvements for Kinesis stream configuration, including multi-account support and trusted account features, integrating these changes with Terraform. Their work focused on enhancing data processing and infrastructure components.
realtimerealtime-dataserverlessaws-lambdaaws
javefang/pyaqara
Dec 2016 - Jan 2020
Contributions:8 releases, 141 commits, 16 PRs in 3 years
python-implementationpythonaqara
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