Alvaro Mariano is a Senior Software Engineer with 11 years of experience building scalable backend systems and shipping high-impact features across fintech and marketplace platforms. Currently at Venmo, he focuses on Python/Django services, Kubernetes/Helm standardization, and performance improvements, having driven Python upgrades and local container ergonomics. His background includes growth and experiment-driven work at Uber Eats and payments and search optimizations at Cornershop, where he reduced operational cost and improved search accuracy. He’s contributed to open-source projects that make Brazilian government gazettes accessible and improved a popular Django notifications library, showing a practical bent for data extraction and maintainable backend tooling. Based in Santa Catarina, Brazil, he combines hands-on engineering with experience leading small teams and integrating numerous partners into high-availability, data-heavy systems.
12 years of coding experience
8 years of employment as a software developer
Bachelor in Computer Science, Computer Science, Bachelor in Computer Science, Computer Science at Universidade Estadual de Mato Grosso do Sul
Contributions:8 releases, 6 reviews, 59 commits in 1 year 1 month
Contributions summary:Alvaro primarily contributed to the back-end development of the Django notifications app. Their commits involved fixing bugs, improving existing features, and adding new functionalities, such as the ability to filter notifications by recipient. They also refactored code and updated the project to support newer Django versions. These changes demonstrate a focus on improving the core functionality and maintainability of the notification system.
📰 Diários oficiais brasileiros acessíveis a todos | 📰 Brazilian government gazettes, accessible to everyone.
Role in this project:
Backend Developer
Contributions:9 commits, 1 PR, 4 comments in 28 days
Contributions summary:Alvaro primarily contributed to the project by adding and modifying spiders, which suggests a focus on data collection and scraping. They implemented a new spider for Campo Grande, MS, and made adjustments to an existing pipeline for processing PDF files. The commits demonstrate a focus on extracting data from governmental gazettes. Further contributions include implementing changes suggested by other contributors.
pythoncivic-techdata-sciencegazette-crawlerspider
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