# Varun S. > Software Engineer @ Quotient |📍San Francisco, CA Location: San Francisco, California, United States Profile: https://flows.cv/varuns As a Software Engineer at Quotient Technology Inc., I design and develop nano-services for the company's digital promotions platform, using Java, SpringBoot, GCP, and GKE. I spearheaded the development and porting of a revenue-critical nano-service that processes user transactions, ensuring data accuracy and reliability. I have completed my Master of Science in Computer Science at UC Riverside, where I gained in-depth knowledge of Cloud Computing, Big Data and Distributed Systems. I have also applied my skills and knowledge as a Big Data and Cloud Engineer Intern at Rakuten Americas, a Senior Software Engineer at ZopSmart and a Computer Vision Engineer at DeepSight AI Labs. I have a demonstrated history of problem-solving, fast learning. I am interested in exploring new challenges and opportunities in the tech industry, and I strive to maintain a high quality in all my endeavors. ## Work Experience ### Software Engineer @ Quotient Technology Inc. Jan 2023 – Present | San Jose, California, United States • Designed and developed revenue generating RESTful APIs for the company’s digital promotions platform in Java/SpringBoot. • Spearheaded the development and maintenance of a revenue-critical transactional API responsible for processing promotions redeemed by users, ensuring data accuracy and reliability. • Played key roles in design and development decisions for a cloud based solution by effectively using tools such as Dockers, Google Kubernetes Engine, CloudBuild, PubSub, Redis MemoryStore, Compute Engine, ArgoCD, Spinnaker and monitor- ing tools such as Splunk and Grafana. • Collaborated and co-ordinated efforts between a global team for the seamless migration of several services from On-Prem to the Cloud Computing solution. ### Teaching Assistant @ University of California, Riverside Jan 2022 – Jan 2022 | Riverside, California, United States Teaching Assistant for CS061 “Machine Organization and Assembly Language” ### Big Data and Cloud Engineer Intern @ Rakuten Americas Jan 2022 – Jan 2022 | San Mateo, California, United States • Designed and developed from scratch a config-driven ETL data pipeline for reducing the volume of application-level metric logs produced by multiple jobs of varying formats. • Single pipeline with an event-based listener to parse the logs from all jobs and combine these logs using aggregation techniques in Dataflow before writing them to the analytics layer - BigQuery. • Created a Google DataStudio dashboard for automated summary reports and insights into the logs being stored. • Achieved an 85% reduction in data volume which resulted in a 99% reduction in the cost of querying, retrieval, and storage of the logs due to the efficiency of BigQuery. • Implemented using GCP tools - PubSub, Dataflow, BigQuery, DataStudio - in the Java SDK, and Maven. ### Computer Science Grader @ University of California, Riverside Jan 2022 – Jan 2022 | California, United States Grader for CS141 - "Intermediate Data Structures & Algorithms" ### Senior Software Engineer @ ZopSmart Jan 2021 – Jan 2021 | Bengaluru, Karnataka, India • Built services and tools using Golang for a North American Retail Giant’s B2C e-Commerce platform. • Designed and developed from scratch an automated data migration framework and tool for easy migration, transformation and filtering of data between different data sources. The tool was used internally by all teams. Supported Data Sources : CSV, JSON, MySQL, Postgres SQL, MS SQL, Cassandra, Yugabyte, Apache Kafka (with Avro encoding), Google PubSub, Eventhub, MongoDB, Elastic Search, Solr • Enhanced the usually linear data pipeline to enable multiple data inputs and outputs as well as complex and arbitrary internal dataflows using graph theory. ### Software Engineer @ ZopSmart Jan 2020 – Jan 2021 | Bengaluru, Karnataka, India ### Software Engineer - Computer Vision @ DeepSight AI Labs Jan 2018 – Jan 2020 | Bangalore, India • Played a key role in end-to-end development of the product – the “GoDeep” platform, neural network, and setup - by implementing concepts of Full Stack Engineering, High Performance Computing and Linux based Product Development. • Developed and implemented an adaptable and highly scalable approach to Inferencing, Training and Validation of the Neural Network which improved the speed severalfold. • Improved the performance of the platform by orders of magnitude by heavily parallelizing key computational loads and by isolating and removing memory and compute bottlenecks. • Played a key role in strategizing and extensively improving the push-button installation procedure of the product by implementing robust OS level methodologies and security practices. • Designed and Developed a server solution of the Platform to serve highly scalable demand using concepts of Asynchronous Processing: Remote Procedural Calls, Message Queues, and Scalable Worker Processes. (using Golang and Python, deployed on AWS EC2) • Contributed to solving key problems and providing innovative solutions during high stake engineering and client meetings. ### Research Student @ PES University Jan 2016 – Jan 2018 | Centre for Cloud Computing and Big Data Worked on research projects with Dr. KV Subramaniam during my time at CCBD. ### Summer Research Intern @ Binghamton University Jan 2017 – Jan 2017 | Binghamton, NY • The project aimed to address the sub optimal power management of datacentres by dynamically managing the incoming requests between groups of servers according to their power consumption. • I was responsible for the design and implementation of the power management module using C ## Education ### Master of Science - MS in Computer Science University of California, Riverside ### Bachelor of Technology - BTech in Computer Science PES University ### National Public School ## Contact & Social - LinkedIn: https://linkedin.com/in/varunsapre --- Source: https://flows.cv/varuns JSON Resume: https://flows.cv/varuns/resume.json Last updated: 2026-03-29