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Egor Ryashin has been working in the software engineering field since 2005. Egor began their career as a Java Developer at Devexperts, where they enhanced account statement Java Swing UI and reprogrammed its EJB layer routines, as well as introduced futures mark to market calculation. Egor then moved on to developing Thinkpipes trading platform, where they reprogrammed it to use the new financial symbology OSI standard and introduced calculation of various financial indicators. Egor also provided support and development of a monitoring distributed application, utilizing C/C++, Perl, Bash, network protocols, JMX, Java, JDBC, JSP, Servlets, Tomcat, Apache HTTP, and Linux. In 2015, they became a Professional Freelancer, participating in multiple projects using JavaFx 8, Spring, JavaScript 5/6, HTML5, CSS3, D3.js, and Paper.js. In 2016, they joined Metamarkets as a Software Engineer, working on software engineering of a big data processing and analytics platform for the adtech industry. Egor contributed to Druid NoSQL distributed database development, cost reduction of Spark and Druid clusters and data segments storage, Druid and Mesos integration, Mesos monitoring, and the migration of Druid Theirtorical cluster from AWS to GCP. In 2019, they joined FacetData as a Software Engineer, and in 2020, they moved to Rill Data, where they are currently working as a Software Engineer. At Rill, they are working on the world’s first truly elastic, fully managed cloud service for Apache Druid.

Egor Ryashin's education history includes a Bachelor and Master degree in Computer Science and Information Security from St. Petersburg State Polytechnical University, obtained between 2000 and 2007. Egor has also obtained certifications from Pluralsight, HackerRank, Coursera, and Angelika Langer. These certifications include Developing Applications on Ethereum Blockchain, Exploring Go Modules, Concurrent Programming with Go, Rust Fundamentals, Developing Applications with AWS Lightsail, Problem Solving (Advanced), Functional Programming Principles in Scala, Algorithms: Design and Analysis, Part 1, Statistical Inference, Machine Learning, High-Performance Java, SCJP 1.5, and SCJP 1.6.