Xiaoyong Zhang
Software Engineer at Idea Media International
Redwood City, California, United States
Summary
🤩
Rockstar🎓
Top SchoolXiaoyong Zhang is a seasoned software engineer with 11 years of experience based in Redwood City, California, currently developing at Idea Media International. He brings strong backend and DevOps chops demonstrated by contributions to the popular feathr-ai/feathr project, where he improved Databricks and Azure Synapse integrations, refactored code to adopt the Databricks CLI, and streamlined provisioning scripts to boost cross-environment usability. Prior experience as a database administrator gives him a solid grounding in data reliability and operational best practices, helping him bridge engineering and infrastructure concerns. Known for improving code quality and documentation, he focuses on practical, production-ready solutions that simplify developer experience.
11 years of coding experience
BS
Github Skills (13)
azure-synapse10
databricks10
spark10
python10
devops9
bash8
git8
feature-engineering7
microsoft-azure7
apache-spark7
azure7
mlops5
machine-learning5
Programming languages (14)
Github contributions (5)
feathr-ai/feathr
Mar 2022 - Jan 2023
Feathr – A scalable, unified data and AI engineering platform for enterprise
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:1 release, 805 reviews, 111 commits in 10 months
Contributions summary:Xiaoyong's contributions focused on enhancing the Feathr platform's compatibility and usability across various environments, including Databricks and Azure Synapse. They implemented and tested features for Databricks integration, as well as made changes to the Azure resource provisioning scripts. In addition to backend improvements, the user also removed dependencies and fixed documentation issues, suggesting a focus on improving overall code quality and user experience. The user also refactored code to use the Databricks CLI.
feature-storedata-qualitydata-scienceenterprise-grademlops
microsoft/AzureML-BERT
Dec 2018 - Jun 2020
End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service
Contributions:13 commits, 4 PRs, 14 pushes in 1 year 6 months
bertfinetuningtrainingbert-fine-tuninglanguage-model
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