About

Vamshidhar Behara is a highly skilled Senior Software Engineer with over 11 years of experience in developing and architecting backend systems for large-scale features and services. He is currently employed at Twitter, where he utilizes his technical expertise to design and develop microservices using a variety of programming languages, including Ruby, Java, C#, Python, C/C++, PHP, and SQL. Vamshidhar is well-versed in a range of frameworks and tools, including Ruby on Rails, Memcache, Redis, Resque, AWS EC2, Unicorn, Statsd, Nagios, AWS ElasticCache, AWS RDS, Spring, Akka, ElasticSearch, Mongoid, Django, .NET, WCF, Protocol Buffers, RabbitMQ, Web Services, React.js, Javascript/jQuery, RSpec, JUnit, NUnit, Cucumber, Apache Hadoop (MapReduce), Apache Tomcat, Git, JIRA, Jenkins, Maven, Rubymine, IntelliJ IDEA, and Visual Studio. Vamshidhar has worked with a number of notable companies throughout his career, including Zynga, where he served as a Principal Software Engineer. During his time at Zynga, Vamshidhar was responsible for architecting and leading backend design and development for large-scale features and services that powered the With Friends network of games. He played a key role in launching Words With Friends 2, which reached #1 in Top Free Apps on iOS and Android App stores. Vamshidhar also designed and developed real-time game stats for With Friends games that process 20M moves/minute, replacing an existing stats system that was expensive to run and only updated once a day. Additionally, he architected, designed, and developed a cross-promotion system for With Friends games, which helped to launch two new games, Boggle and Crosswords With Friends. Prior to joining Zynga, Vamshidhar worked as a Software Engineer at Indigo BioAutomation, Inc., where he developed the company's flagship product, Ascent, a web-enabled automated chromatographic analysis and review system. He implemented features for Ascent using Ruby, Rails, MongoDB, RSpec, and Cucumber with TDD/BDD. Vamshidhar also developed WCF services to support workflow between instrument machines and Ascent servers, optimized mongo queries and data transfer points to achieve a 20,000% improvement in data review speed in Ascent, and