Andrei Medvedev

I am a backend software engineer at Microsoft, one of the world's largest IT companies, where I focus on developing scalable solutions to support various Microsoft products. My role involves optimizing backend systems in Bing local search. Working at Microsoft has deepened my expertise in windows platform tooling, and I am engaged with the latest advancements in the field.

At Yandex, Russia's largest tech company, I have developed a deep understanding of cutting-edge technology. My role allowed me to work in a fast-paced environment, refining my skills in machine learning, networking, large distributed systems, realtime processing and data analysis. This background has equipped me with a perspective that I bring to every new project, ensuring efficient, effective, and forward-thinking solutions.

Previously, I worked at Gridgain, where I specialized in distributed caching when developing Apache Ignite for Sberbank, the largest bank in Russia. This role involved managing high-volume data and addressing concurrency challenges. My work focused on JVM profiling, using custom tooling, and solving critical platform issues through in-depth post-mortem analysis and debugging. I was also responsible for bug fixing and acted as a liaison with the remote core team, providing 3rd-level support to systems administrators. This experience strengthened my expertise in distributed systems and performance optimization.

My areas of expertise cover a comprehensive range of skills.

• Backend engineering
• Networking
• Data analytics (SQL)

My technical foundation is built on the use of compiled languages, especially Go, which I've used for many years, alongside C++, Java, and Clojure. I prefer the Linux ecosystem for servers, Mac for desktop and Jetbrains software for editing the code.

In addition to my in-house programming roles at companies like Microsoft and Yandex, I've successfully completed freelance projects that showcase my versatility across various areas and project types.

Messengers data extraction

Recently, I developed solutions for messaging platforms like Telegram, to enable data processing, analysis, and machine learning applications. Leveraging native tools, I can access, clean, and structure data from these platforms.

Mobile application (iOS)

Between 2019 and 2022, I developed and hosted an iOS application on the Apple App Store to deliver real-time air quality index data, aggregating information from multiple sources to provide users with accurate, location-based insights. It had versions for iPad and iPhone

Interested in learning more about my background and expertise? Download my resume to view a detailed overview of my technical skills.

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