Farooq Qaiser
Senior Software Engineer at The Apache Software Foundation
Mississauga, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolFarooq Qaiser is a Senior Software Engineer with nine years of experience building large-scale, real-time data platforms and streaming infrastructure. He has designed and operated Kafka- and Flink-based pipelines at scale—most recently for Shopify—and has deep hands-on experience with Iceberg, Spark, Kubernetes and cloud-native tooling. An active Apache contributor, Farooq has improved Spark SQL internals (notably struct column APIs) and contributed to Kafka, Iceberg and Flink projects, demonstrating both production-grade engineering and attention to API correctness. He pairs a data-first engineering mindset with practical product delivery, having moved monolithic batch systems to event-driven architectures and ingested petabytes into analytical stores. Based in Mississauga, Ontario, he combines formal training from LSE with continued learning in applied machine and autonomous systems, bringing a cross-disciplinary curiosity to distributed systems work.
9 years of coding experience
8 years of employment as a software developer
Self Driving Car Engineer Nanodegree - Term 1, Self Driving Car Engineer Nanodegree - Term 1 at UdacityLondon School of Economics and Political Science
Github Skills (7)
javas10
big-data10
spark10
sql10
java10
scala10
jdbc5
Programming languages (5)
Github contributions (5)
apache/spark
Dec 2019 - Sep 2020
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:36 reviews, 4 PRs, 138 comments in 9 months
Contributions summary:Farooq primarily contributed to the Spark SQL module, focusing on enhancing the `Column` class with new methods for manipulating struct fields. Their work involved implementing `withField` and `dropFields` methods, allowing users to add, replace, and remove fields within nested struct columns. The user also fixed a bug related to the `withField` method in the optimizer, ensuring correct behavior when operating on null struct columns and improving the overall consistency of the API. Their contributions included writing and updating unit tests to validate the functionality and correctness of the changes.
analyticspythondata-processingsqlapache
fqaiser94/mse
Jan 2020 - Mar 2020
Make Structs Easy (MSE)
Contributions:5 releases, 78 commits, 32 PRs in 2 months
msestructs
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.