Praveenkumar Venkatesan
Principal Software Engineer at Apple
California, United States
Summary
🤩
Rockstar🎓
Top SchoolPraveenkumar Venkatesan is a Principal Software Engineer based in California with 11 years of experience building large-scale, product-driven systems across iOS, real-time analytics, ML, and video. He combines hands-on engineering with cross-functional leadership, having shipped award-winning mobile apps, architected near-real-time Kafka/Hadoop pipelines processing billions of events daily, and led migrations to databases like Apache Druid to improve analytics performance. At Yahoo and Apple he drove initiatives spanning Node.js microservices, privacy compliance, and ML-based alerting, and he contributes to open-source projects such as Apache Druid (notably improving time zone and timestamp handling). An entrepreneur at heart, he occasionally launches side products used by over 50k monthly users and mentors teams from interns to senior engineers. His favorite intersection is strategy, design, engineering and product—where he rapidly turns ideas into impactful launches.
11 years of coding experience
8 years of employment as a software developer
Master of Science (M.S.), Computer Engineering, Master of Science (M.S.), Computer Engineering at Carnegie Mellon UniversityBachelor of Science (BS), Computer Engineering, Bachelor of Science (BS), Computer Engineering at Oklahoma State University
English
Stackoverflow
1,811reputation
655kreached
2answers
44questions
Github Skills (14)
javas10
apache-druid10
indexing10
java10
data-structure9
data-structures9
c-string6
caching6
camera6
coreanimation6
browser6
apache-kafka6
controller6
ruby6
Programming languages (4)
Github contributions (5)
apache/druid
Oct 2016 - Oct 2017
Apache Druid: a high performance real-time analytics database.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 21 PRs, 89 comments in 1 year
Contributions summary:Praveenkumar primarily contributed to enhancing the Apache Druid database's core functionalities. Their work included adding timezone support to segment granularity, which involved modifying core Java files related to indexing and data handling. They also focused on improving the internal data structures by using timestamps in milliseconds as map keys instead of DateTime objects, improving performance. Furthermore, the user worked on handling null timezone during equals check and documenting the changes.
real-timebig-datadruiddatabasehadoop
praveev/airflow
Dec 2015 - Jan 2016
Contributions:2 PRs, 15 pushes, 10 branches in 1 month
monitorpythondata-sciencedata-pipelinesprogrammatically
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.