Matt D'Souza


This information is also available in my resume and on Linkedin.

Software Engineering Intern | Facebook | Seattle, WA (Remote) | June-August 2020
I worked on the Unified Programming Model team, where I built a best-effort translator between Presto and Spark SQL.
Software Engineering Intern | Facebook | New York, NY | September-December 2019
I worked on the Mobile Product Runtimes team, where I built utilities to understand the output of various transformations/optimizations Facebook applies to Android APK and DEX files. In particular, I built and optimized a tool to generate semantic diffs between APKs.
Software Engineering Intern | Facebook | Menlo Park, CA | January-April 2019
I worked on Pyre, Facebook's open-source type checker for Python 3, where I improved IDE integration and designed a more efficient build process for Python projects built with Buck.
Software Engineering Intern | Snowflake Computing | San Mateo, CA | May-August 2018
I worked on the Data Platform team, which was responsible for developing the client drivers and connectors used by BI, ETL, and other tools to connect to the Snowflake database. I implemented features spanning the backend and client drivers, including multi-statement support and a safer way to handle large array binds.
Relevancy Engineering Intern | Wish | Toronto, ON | September-December 2017
I worked on the Relevancy Engineering team in Toronto. In this role, I worked on infrastructure to support backup, restore, and synchronization of certain in-memory (Redis) and graph (TigerGraph) databases. I also developed data pipelines used by Wish's recommendation system.
Data Platform Engineering Intern | Shopify | Toronto, ON | January-April 2017
I worked on Shopify's Data Acquisition team, developing systems to extract and consolidate raw data from numerous sources into our data lake.
Software Engineering Intern | Veeva Systems | Toronto, ON | May-August 2016
I worked on the full stack of Veeva's Network Customer Master product. A significant portion of my work was in implementing usage tracking throughout the front- and back-end to identify user behaviour and performance.