Rithika Pagilla

Mountain View, California, United States

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Summary

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Rockstar

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Top School

Rithika Pagilla is a cloud-focused software engineer with three years of experience building data pipelines and backend systems, currently based in Mountain View, CA. She has hands-on expertise with AWS serverless architectures—Glue, Lambda, Step Functions, S3—and has processed over 500K IoT records daily while tuning Redshift models and deploying reproducible pipelines via Docker and CodePipeline. On the backend side she has contributed to the widely used Apache Kafka project, improving partition assignment, rack-aware replica placement, and the PartitionAssignor interface to boost stability and scalability. Comfortable bridging research and production, she built a Flask analytics layer tied to Athena/QuickSight for KPI visualization and applied schema enforcement to improve dataset reliability. Rithika pairs academic training in information technology with practical experience delivering end-to-end data solutions in enterprise and open-source distributed systems.

3 years of coding experience

1 year of employment as a software developer

masters, Information Technology, masters, Information Technology at University of Cincinnati

English, Telugu, Hindi

Github Skills (8)

server-side10

javas10

kafka10

partitioning10

server10

java10

scala10

api-design9

Programming languages (1)

Java

Github contributions (3)

apache/kafka

Feb 2023 - Apr 2026

Apache Kafka - A distributed event streaming platform

Role in this project:

Back-end Developer

Contributions:751 reviews, 58 PRs, 766 comments in 3 years 2 months

Contributions summary:Rithika primarily worked on enhancing the server-side logic of Apache Kafka, specifically improving the group coordinator and partition assignment functionalities. Their contributions involved refactoring the `PartitionAssignor` interface and implementing a range assignor on the server-side. They also made modifications to support rack-aware replica placement and optimized the uniform rack-aware assignor. These changes focused on improving stability, efficiency, and scalability of the system.

apache-kafkascalakafkajavastreaming

rreddy-22/kafka-rreddy

Mar 2023 - Mar 2026

Mirror of Apache Kafka

Contributions:377 pushes, 62 branches in 3 years

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