Pranav Anand
Software Engineer at Instagram
New York, New York, United States
Summary
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Rockstar🎓
Top SchoolPranav Anand is a software engineer with 11 years of experience building scalable backend systems, currently focused on reducing teen harm at Instagram. He spent several years at Databricks working on Delta, ingestion, and streaming engines, and contributes to the widely used open-source Delta Lake project by improving exception handling, option verification, and test modularity. Pranav brings a strong practical background in distributed data systems and media infrastructure from internships at WhatsApp and Spark work at Databricks, along with hands-on attention to developer experience through technical writing for MLflow documentation. Based in New York and trained at the University of Waterloo, he blends deep engineering rigor with a knack for making complex systems more reliable and easier to maintain.
11 years of coding experience
5 years of employment as a software developer
Bachelor's Degree Computer Science, Bachelor's Degree Computer Science at University of Waterloo
French, Hindi, English
Stackoverflow
13reputation
1kreached
0answers
3questions
Github Skills (16)
scala10
testing10
big-data10
mlflow10
spark10
delta-lake10
documentation10
analytics9
rs9
user-manual8
acid8
basics8
learn-ruby-on-rails8
eclipse6
android6
Programming languages (4)
Github contributions (5)
delta-io/delta
Apr 2019 - Sep 2022
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 1 review, 35 commits in 3 years 5 months
Contributions summary:Pranav Anand contributed to the `delta-io/delta` repository by refactoring and improving exception handling, specifically by modifying exceptions to include table names and paths. They also implemented and tested a verification method for `DeltaOptions` to check and log invalid options passed by users, adding tests for different scenarios. Furthermore, the user refactored tests to make them easier to extend by splitting utility methods into a separate trait, promoting code reusability.
analyticsprestodbflinkbig-dataspark
mlflow/mlflow
Jun 2018 - Jan 2020
Open source platform for the machine learning lifecycle
Role in this project:Technical Writer
Technical WriterContributions:47 commits in 1 year 7 months
Contributions summary:Pranav's contributions primarily involved improving the documentation of the MLflow project. The commits focused on fixing typos, correcting third-party names, standardizing the treatment of code blocks, and addressing formatting inconsistencies. The user also added and updated screenshots, making the documentation more user-friendly and visually appealing. These changes suggest a focus on clarifying the project's documentation.
pythonlifecyclemlmachine-learningincremental-learning
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