Danil Nurgaliev
Senior Software Engineer at Workato
Tbilisi, Georgia
Summary
🤩
Rockstar🎓
Top SchoolDanil Nurgaliev is a Senior Backend Engineer with 11 years of experience, specializing in Ruby and increasingly in Go, who focuses on distributed systems, performance optimization, and observability. He has a strong track record migrating large monoliths to microservices and building scalable, maintainable architectures across startups and consultancy engagements at Toptal and Workato. Danil has contributed to notable open-source tooling in the Ruby ecosystem—improving the toptal/chewy Elasticsearch framework by hardening pagination, async cleanup, and release stability—which reflects his attention to data integrity and operational robustness. Comfortable across Kafka, Redis, Postgres, GraphQL, Kubernetes and Docker, he blends deep backend engineering with practical DevOps sensibilities. Based in Tbilisi, he brings a mathematician’s rigor from his engineering studies to solving complex production problems and mentoring teams through architectural change.
11 years of coding experience
10 years of employment as a software developer
Диплом специалиста по инженерной специальности, Инженер Математик, Диплом специалиста по инженерной специальности, Инженер Математик at Kazan State Energy University
Русский, Английский
Github Skills (9)
ruby10
elasticsearch-client10
elasticsearch10
elasticsearchquery10
aws-elasticsearch10
elasticsearch-api10
amazon-elasticsearch10
rake9
rspec8
Programming languages (6)
Github contributions (5)
toptal/chewy
Oct 2021 - Dec 2022
High-level Elasticsearch Ruby framework based on the official elasticsearch-ruby client
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 releases, 53 reviews, 9 commits in 1 year 2 months
Contributions summary:Danil primarily focused on improving the Chewy framework's functionality and stability. Their contributions included fixing pagination issues in the journal, adding asynchronous options for journal cleanup, and preparing releases. The user also addressed potential data loss risks by implementing warnings related to missing journal indices and provided enhancements to the rake tasks. Furthermore, the user added functionality for asynchronous journal clean-up.
ruby-frameworkelastichigh-levelruby-clientruby
konalegi/ar_lazy_preload
Sep 2020 - Dec 2022
Lazy loading associations for the ActiveRecord models
Contributions:1 review, 2 PRs, 18 pushes in 2 years 4 months
railsrubyactiverecord-modelslazy-loadingactiverecord
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