Alejandro Gonzalez-araya
Software Engineer at Microsoft
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolAlejandro Gonzalez-araya is a Software Engineer based in Seattle with a decade of experience building cloud-native platforms and developer tooling. He currently works on Azure App Service for Linux at Microsoft, focusing on PaaS and serverless capabilities that help teams deploy and run containerized and web workloads. Alejandro has a strong full-stack background demonstrated by contributions to the popular sparkmagic Jupyter project, where he improved UX for interacting with remote Spark clusters and added SQL/Hive result handling and visualizations. He holds an MS in Computer Engineering from the University of Puerto Rico–Mayagüez and brings both systems-level rigor and user-focused product thinking to his work. Known for bridging backend integration with intuitive front-end controls, he excels at turning complex distributed systems features into accessible developer experiences. Colleagues rely on him for pragmatic solutions that smooth the path from data exploration to production.
10 years of coding experience
Master of Science - MS, Computer Engineering, Master of Science - MS, Computer Engineering at University of Puerto Rico-Mayaguez
Github Skills (6)
pandas10
jupyter-notebook10
spark10
sql10
python10
ipywidgets9
Programming languages (8)
Github contributions (5)
jupyter-incubator/sparkmagic
Sep 2015 - Nov 2017
Jupyter magics and kernels for working with remote Spark clusters
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:381 commits, 309 PRs, 430 pushes in 2 years 1 month
Contributions summary:Alejandro's contributions center around enhancing the user interface and integrating features related to remote Spark cluster interaction via Jupyter notebooks and Python. The user added the ability for users to add and manage session configurations and for SQL and Hive queries, creating user-friendly controls and visualizations based on the results. They implemented mechanisms to handle and display results from SQL queries, including automatic visualizations for data analysis. These commits reflect a focus on the user experience and integration with the underlying Spark infrastructure.
kernelclustersjupyter-notebookmagickernels
aggFTW/sparkmagic
Oct 2015 - Nov 2015
Contributions:50 pushes, 7 branches in 19 days
clustersipythonpythonspark
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