Vitor Avila

Sales Engineer at Preset

Rio Grande do Sul, Brazil
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Summary

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Vitor Avila is a Technical Support Manager with a strong blend of application support and electronics background, bringing over four years of hands-on troubleshooting and three years in software-focused roles. He progressed through customer-facing and escalation engineering roles at Preset and e-Core, building expertise in cloud environments, databases, DevOps collaboration, and incident management. Vitor pairs a passion for customer success with a knack for automation and knowledge-base creation, reducing repeat incidents and improving team efficiency. An active back-end contributor to the popular Apache Superset project, he has fixed data-import bugs and hardened column/metric behaviors, showing he still writes code to solve real support problems. Based in Rio Grande do Sul, Brazil, he also founded and ran an audio repair business, giving him practical experience in product maintenance, customer care, and cross-disciplinary leadership.
code4 years of coding experience
job8 years of employment as a software developer
bookTechnician Electrical and Electronics Engineering, Technician Electrical and Electronics Engineering at Faculdade de Tecnologia SENAI Porto Alegre
bookTechnologist System Analysis and Development, Technologist System Analysis and Development at FADERGS
languagesPortuguese, English
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Stackoverflow

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Github Skills (16)

apache-superset10
python10
sql9
data-visualization8
data-visualisation8
data-visualizations8
flask8
flask-ask8
testing7
pytest7
data-analysis7
data-analytics7
databases6
database6
data-engineering6

Programming languages (4)

TypeScriptRustMarkdownPython

Github contributions (5)

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apache/superset

Jul 2022 - Jul 2026

Apache Superset is a Data Visualization and Data Exploration Platform
Role in this project:
userBack-end Developer
Contributions:307 reviews, 171 PRs, 218 pushes in 4 years 1 month
Contributions summary:Vitor primarily contributed to fixing bugs and improving the functionality of the Apache Superset platform. Their work involved supporting empty strings in dataset imports, adding logic to check datasets used by filters, including additional fields to export/import commands, updating Snowflake connection placeholders, and supporting importing a database connection with a version set. They also worked on avoiding column denormalization, adding tests to the column denormalization flow, updating the column/metric names for ORDER BY, and improving support for tags with colons.
apache-supersetdata-explorationdata-visualizationsupersetapache
preset-io/embedded-example

Oct 2023 - Apr 2026

Sample (and extremely simple) Flask app that can be used to test the Preset Embedding experience!
Contributions:1 review, 9 PRs, 11 pushes in 2 years 5 months
flask
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