Fernando Lisboa
Software Engineer at Google
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolFernando Lisboa is a software engineer in San Francisco with six years of experience building systems-focused infrastructure, databases, and machine learning tooling. He has hands-on backend and database experience, contributing to core MongoDB server code—touching command/pipeline interfaces, catalog operations, views, and multi-tenancy—and has applied similar distributed-query work during an internship on Google’s F1 Query. Fernando’s background spans high-performance data pipelines for satellite imagery at SpaceML, trading systems at IMC, and teaching database and distributed-systems courses at Carnegie Mellon, reflecting both research breadth and production rigor. Now at Google, he brings a practical blend of systems design, low-level engineering, and ML-aware tooling to large-scale services. Colleagues value his tendency to tackle thorny core-system changes that unlock broader platform capabilities rather than only surface features.
6 years of coding experience
3 years of employment as a software developer
High School Diploma, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES, High School Diploma, HIGH SCHOOL/SECONDARY DIPLOMAS AND CERTIFICATES at Benet AcademyBachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Carnegie Mellon University
Portuguese, English
Github Skills (14)
databases10
cpp10
cplus10
mongodb10
nosql10
mongodb-database10
database10
multitenancy8
multi-tenant8
apidoc7
api7
sys6
system-design6
software-design6
Programming languages (3)
Github contributions (5)
mongodb/mongo
Jun 2022 - Aug 2022
The MongoDB Database
Role in this project:
Back-end Developer / Database Engineer
Back-end Developer / Database EngineerContributions:11 commits in 2 months
Contributions summary:Fernando primarily focused on modifying and extending the MongoDB database codebase. Their contributions involved changing database-related functions and interfaces, specifically around the use of `DatabaseName` and related types. Key changes included updates to command structures, pipeline interfaces, and catalog operations, directly impacting database operations. The user also modified code related to views and tenant migrations, showing involvement in data management and multi-tenancy features.
nosqlc-plus-plusmongodb-databasedatabasemongodb
spaceml-org/GIBS-Downloader
Jan 2021 - Jan 2022
GIBS Downloader is a command-line tool which facilitates the downloading of NASA satellite imagery and offers different functionalities in order to prepare the images for training in a machine learning pipeline.
Contributions:6 reviews, 109 commits, 9 PRs in 11 months
satellite-imagerypythontrainingpreparefacilitates
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.