About

Preetansh Goyal is a highly skilled Software Engineer with over 4 years of relevant experience in the industry. He is currently employed at Google as a Software Engineer, where he works on optimizing the latency of 'Read' queries and disk usage in Google's Time-Series database. He has also improved the existing data compaction process to scale the dataset while dealing with frequent job preemption of compaction jobs and designed batch-jobs to periodically perform consolidation on live data through latch-free time-series demarcation. His efforts have resulted in a ~50% reduction in database size after compaction, bringing disk usage from 3.3 PiB to 1.6 PiB. Prior to his current role, Preetansh worked as a Software Engineer Intern at Google, where he contributed to the redesign of series-data compaction in Google's Time-Series database. He has also worked as a Software Development Engineer 2 at Adobe, where he was responsible for developing new camera pipelines with augmented image modification filters using OpenGL and RenderScript. He managed multiple modules responsible for the creation of graphic assets using camera feed or images and developed features for generating Colored Vector Patterns using raster images captured through the camera. Preetansh holds a Masters in Computational Data Science from Carnegie Mellon University and a Bachelor of Technology (B.Tech.) in Computer Science and Engineering from IIT. He also has a High School Diploma from St. Aloysius Sr. Sec. School, Jabalpur. His tech stack includes Software Engineering, Android, and testing. Overall, Preetansh is a highly motivated and skilled Software Engineer with a passion for optimizing systems and improving user experiences. He is always looking for new challenges and opportunities to learn and grow in his field.