Personal details

Amanbolat B. - Remote back-end developer

Amanbolat B.

Based in: 🇩🇪 Germany
Timezone: Berlin (UTC+2)

Summary

🚀 Hello there! I'm a Staff Software Engineer who loves to turn coffee into code. With over a decade of experience in the industry, I've got my hands dirty with everything from backend development to DevOps, frontend, mobile, and even a little AI and NLP. I've led teams, tamed startups, and navigated the seas of large enterprises. I speak Go fluently, but I'm also conversational in a smorgasbord of other languages, including TypeScript, JavaScript, C++, Java, Python, and Swift.

💡 I've worked on projects that would make your head spin - from developing multi-region distributed systems at Delivery Hero to leading the development of huge B2B enterprise systems. I've even gotten my hands dirty with a legacy monolith projects, transforming it into a sleek, modern microservice architecture written in Go.

Work Experience

Staff Software Engineer
Delivery Hero | Dec 2023 - Present
Python
MongoDB
Google Cloud Platform
Kubernetes
Go (Golang)
AWS (Amazon Web Services)
  • Introduced multi-region deployment strategy for multiple services in AdTech.
  • Worked on decomposition of a complex monolith and moving to micro service architecture with zero downtime.
  • Mentoring backend developers and promoting best practices.

Education

University of International Business and Economics
Bachelor's degree・Management
Sep 2010 - Jun 2014

Personal Projects

CAT Tool Framework
2017
Java
JavaScript
Go (Golang)
This project aimed to develop a collection of autonomous modules for creating Computer-Assisted Translation tools. The key distinguishing factor from competitors lies in the rapid document processing capabilities and the prioritisation of system complexity over support for outdated document standards.
Realistic Data Generator
2022
Go (Golang)
This tool offers various converters to analyse SQL DDL or OpenAPI specifications and create a versatile data model that is utilised for generating the data. The concept lies somewhere in the middle of AI-driven synthetic data generators and basic random data generators, resulting in a rule-based solution that can surpass other alternatives.