Aug 2022 – Jun 2024 · 1 yr 10 mos · Bengaluru, Karnataka, India

• Delivered 5+ scalability features to major clients for a distributed database, improving PostgreSQL
• compatibility, concurrent transaction isolation and system performance by 20x thus boosting revenue by 10%.
• Enhanced database recovery & fault tolerance by developing Point in Time Restore & X-Cluster Replication.
• Optimized distributed transaction & query performance by 20% by adding support for Materialized Views, Savepoints, Deadlock Detection/Prevention and multiple Transaction Isolation levels using pessimistic locking.
• Developed regression & stress testing framework in multi-threaded Python, reduced test suite runtime by 40%.
• Identified & resolved 50+ critical system regressions, while maintaining compatibility using version control.
• Monitored and triaged automation during on-call, debugging and resolving live issues for smooth operations.
• Recognized with an Impact Award for my work on distributed transaction & automation improvements.
• Worked researching and understanding the implementations of product features and then further doing a quality analysis of them along different parallels of existing features.
• Designed and automated the regression validation and stress suite for the above mentioned features.
• Ensured quality and timely deployment/shipment of all deliverables.
• Handled general product pipeline improvements.

Jan 2022 – Jul 2022 · 6 mos · Bengaluru, Karnataka, India

• Automated testing in Javascript that decreased 2 days worth manual effort during release pipeline to 2 hrs.
• The framework stopped 15+ P0 bugs from going to production, ensuring stable feature deployments.
• Collaborated with cross-functional teams in an agile environment, integrating test automation with GitHub Actions that optimized release pipelines by 50x, saving precious developer time.

Oct 2020 – Jan 2021 · 3 mos

• Worked on creating a model to parse and segregate resumes based on the features like, qualification, skillset, work experience etc. so as to fulfill various job roles available. My contribution was towards parsing resumes and created a dataset in the form of CSV files that could further be processed using machine learning models.
• The final product submitted automatically retrieved resume files from cloud (in various formats i.e. .jpeg .pdf .docx .doc etc.) then parsed them and finally created a CSV file for further processing and segregation.