Janarthanan S
About Janarthanan S
Janarthanan S is a Software Engineer II at GAIN Credit, where he leads projects focused on data retention and automation. He holds a Bachelor of Technology in Information Technology from the College of Engineering, Guindy, and has contributed to various software development initiatives since 2020.
Work at GAIN Credit
Janarthanan S has been employed at GAIN Credit since 2020, initially as a Software Development Intern for two months. He then progressed to the role of Software Engineer I from 2020 to 2022. In 2022, he advanced to Software Engineer II, where he continues to work. His responsibilities include leading significant projects such as the Data Retention project, which involves implementing bulk deletion of customer documents over three years old in S3 buckets, along with backup and restoration options.
Education and Expertise
Janarthanan S studied at the College of Engineering, Guindy, where he earned a Bachelor of Technology (BTech) in Information Technology from 2016 to 2020. His educational background provides a solid foundation for his technical skills in software engineering, particularly in data retention, automation, and microservices.
Technical Contributions
In his current role, Janarthanan S has made several technical contributions. He automated a batch job for future document deletions under the retention policy and played a key role in MySQL data retention efforts. He also developed a RabbitMQ connector module that enables real-time switching between EC2-hosted and AWS MQ queue systems without downtime. Additionally, he integrated payout services from various products into a common payout microservice.
Project Leadership and Achievements
Janarthanan S led the Data Retention project, focusing on the bulk deletion of outdated customer documents. He implemented a proof of concept for migrating the queue system from EC2-hosted RabbitMQ to AWS MQ, which improved operational efficiency by eliminating maintenance man-hours and addressing issues related to clustering and split-brain. His efforts in resolving Django unit test failures significantly increased the success rate from 52% to 100% with minimal code changes.