Wenqi Mou - Software Engineer at Datadog

Wenqi Mou

Software Engineer at Datadog

Salem, Massachusetts, United States

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Summary

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Rockstar

🎓

Top School

Wenqi Mou is a software engineer with eight years of experience building and optimizing large-scale distributed systems at Datadog, PingCAP, Apple, and Dell EMC. She specializes in backend infrastructure, storage, and streaming systems, having contributed notable stability and performance fixes to the open-source Pravega project and engineered the key-value metadata store behind iCloud object storage. Wenqi has a track record of solving production bottlenecks—scaling multi-petabyte clusters, mitigating throttling to increase single-shard throughput 5x, and reducing disk usage by 40% through column-level TTL. Comfortable across cloud-native deployments and low-level client libraries, she also built Kubernetes operators and Rust clients for streaming storage. Based in Salem, MA, Wenqi blends deep debugging instincts with experimental rigor from her Carnegie Mellon master’s background to deliver resilient, high-performance systems.

8 years of coding experience

7 years of employment as a software developer

Bachelor's degree Control, Bachelor's degree Control at Harbin Institute of Technology

Master's degree electrical and computer engineering, Master's degree electrical and computer engineering at Carnegie Mellon University

Chinese, English

Github Skills (13)

data-storage10

javas10

distributed-systems10

distributed-file-system10

java10

streaming-data10

apache-bookkeeper10

streaming9

docker8

kubernetes8

kubernetes-pods8

dockers8

rocksdb7

Programming languages (7)

JavaC++ShellRustCMakeGoPython

Github contributions (5)

pravega/pravega

Mar 2019 - Sep 2021

Pravega - Streaming as a new software defined storage primitive

Role in this project:

Back-end Developer

Contributions:19 reviews, 21 commits, 27 PRs in 2 years 7 months

Contributions summary:Wenqi contributed to the Pravega project by addressing various issues related to the system's back-end functionalities. They updated the Bookkeeper image, fixed external connectivity errors in Kubernetes deployments, and made performance optimizations by making getRemainingBytes asynchronous. Furthermore, the user added features like multi-directory support for ledgers and journals, and also addressed memory leaks. The work demonstrates a focus on improving the stability, performance, and feature set of the distributed streaming storage system.

streaming-datadistributed-storagereal-time-datadefineddata-ingestion

Tristan1900/Budgetier

Jan 2018 - May 2018

Contributions:59 commits, 11 PRs, 52 pushes in 3 months

cdncachessdcaches

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