Quang Nguyen
IT Service Desk And Field Support Officer at nib Group
Sydney, New South Wales, Australia
Summary
🤩
Rockstar🎓
Top SchoolQuang Nguyen is an IT Service Desk and Field Support Officer based in Sydney with nine years of hands-on experience bridging end-user support and backend engineering. While supporting nib Group, he pairs practical IT troubleshooting with contributions to open-source ML infrastructure—most notably as a backend developer and data engineer on Feast, the popular open-source feature store—where he implemented data type fixes, scalable point-in-time joins, proxy-friendly UI changes, and GCS support. He brings a pragmatic blend of network and systems knowledge from formal TAFE certifications and business analysis training, enabling him to translate technical issues into reliable, user-focused solutions. Known for fixing dependency conflicts and optimizing data retrieval, Quang quietly combines service-oriented IT support with meaningful backend contributions that improve production ML workflows.
9 years of coding experience
INTRODUCTORY CERTIFICATE IN BUSINESS ANALYSIS, Business Analysis, INTRODUCTORY CERTIFICATE IN BUSINESS ANALYSIS, Business Analysis at IT MastersCertificate IV, Information Technology Network, Certificate IV, Information Technology Network at TAFE NSWCERTIFICATE III, Information, Digital Media & Technology, CERTIFICATE III, Information, Digital Media & Technology at South Western TAFE Campus
Stackoverflow
16reputation
662reached
1answer
0questions
Github Skills (17)
feature-store10
bigquery10
python10
data-engineering10
pandas10
data-science9
mlops8
kubernetes7
gcp7
kubernetes-pods7
keras6
uid6
deep-learning6
front-end-development6
google-colaboratory6
Programming languages (10)
Github contributions (5)
feast-dev/feast
Jul 2022 - Jan 2023
The Open Source Feature Store for Machine Learning
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:93 reviews, 5 commits, 58 PRs in 5 months
Contributions summary:Quang primarily contributed to the Feast feature store project by addressing bugs and implementing new features related to data type handling, specifically concerning boolean types in Pandas. They worked on applying billing projects for schema inference, and improving point-in-time joining scalability. Additionally, the user implemented features to make the UI accessible behind a proxy and added support for GCS filesystem. The user also fixed dependency version conflicts and optimized bytes processed for entity schema retrieval.
pythondata-qualitydata-sciencemlmachine-learning
sudohainguyen/airflow
Aug 2022 - Apr 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Contributions:67 pushes, 8 branches in 1 year 8 months
monitorapacheprogrammaticallyapache-airflowairflow
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