
Alexander Emelyanov
Verified Expert in Engineering
Software Developer
Saint Petersburg, Russia
Toptal member since August 8, 2014
Alexander is a software engineer who can solve problems and deliver code. He has experience in back-end technologies, like Ruby, Python, Go, C#, C++, Postgres, Redis, Sidekiq, basic ML skills, etc. He is comfortable creating and consuming REST APIs and has developed numerous successful complex services and apps.
Portfolio
Experience
- Docker - 8 years
- Ruby on Rails (RoR) - 8 years
- RSpec - 8 years
- Sidekiq - 8 years
- Ruby - 8 years
- PostgreSQL - 8 years
- Kubernetes - 5 years
- Python - 4 years
Availability
Preferred Environment
Git, Sublime Text, MacOS, ASDF, Oh My Zsh
The most amazing...
...thing I've made is a pack of software to launch a car-sharing startup, including web and car servers, a web UI for customers, and an admin panel for employees.
Work Experience
Senior Software Engineer
Workato
- Moved the job background processing system from Que to Sidekiq, which decreased the main DB load.
- Decreased the integration tests runtime from 50 minutes to 10 minutes.
- Introduced a cache for a recipe code, significantly reducing the main DB load.
- Fixed several bugs with credentials leaking in debug tracing, contributing to customer retention.
Senior Software Engineer
DeepLearn Inc
- Designed and developed the back end, API and management UI for the cluster management system to run our AutoML payload. Developed a couple of related microservices.
- Added the support of RabbitMQ to open source Keda scaler to implement autoscaling in our Kubernetes clusters.
- Implemented an integration test, detecting tens of broken commits.
- Optimized unit tests and made them two times faster.
- Completely fixed false negatives in UI tests by rewriting them from Capybara to Cypress.
- Rewrote 10k CLOC Django project to Rails in ten days and increased test coverage from 80% to 95%.
Lead Software Engineer
Digital Car
- Designed, developed, and supported a car-sharing solution for Colesa.com, a car-sharing service in Saint Petersburg.
- Developed this one-man project and completed it in two months. Created an MVP serving cars and customers. The system worked in production for three years with hundreds of customers and tens of cars.
- Architected the car event machine-based TCP server that collects telemetry and sends control commands to car trackers.
- Created the web server that all business logic and provides APIs for the client's web and mobile applications.
- Built the admin web UI CRM for car-sharing employees to monitor and operate the system.
Senior Software Engineer
SPB TV
- Designed and developed the back end, API, and management UI for the TV streaming platform, OTT middleware.
- Halved the average API response time with optimizations.
- Supported the system in production and handled customer queries.
Software Engineer
VIAcode
- Developed system center operations manager management packs.
- Extended SCOM with a bunch of cool widgets, which were highly appreciated by Microsoft employees.
- Supported Apachi Ambari monitoring tool for Hadoop.
Lead Software Developer
LLC Technologies of Automation
- Designed, developed, and supported an environmental monitoring system.
- Wrote drivers for tens of different hardware devices for data collection.
- Created a report template engine and an accompanying dynamic, extensible API.
Software Developer
Tomsk Electronic Company
- Created an internal tool for the test automation of the legacy software.
- Created tools for pipeline production and counting automation.
- Set up a gateway to provide internet access for all employees.
Experience
Software Solution for a Car Sharing Startup
1. A web server to manage customers and business logic and provide HTTP API for client application
2. A car-server event-machine-based TCP server to collect telemetry and send control commands to car trackers installed inside cars
3. Web UI for customers
4. Admin Web UI for the CRM for car-sharing employees
TV Streaming Platform
https://spbtv.com/case-studies/LebaraPlay.htmlI also halved the average API response time with a bunch of optimizations.
Web Application to manage An Automated Machine Learning Service
I designed and developed the back-end, API, and management UI for this system and some related microservices.
We were blocked from implementing autoscaling for our ML Kubernetes cluster because the Keda auto scaler doesn't have the necessary features.
To solve this, I contributed to Keda and added support for counting unpacked messages in the RabbitMQ scaler. The PR was accepted, and it allowed the company to move forward.
I implemented an integration test that detected tens of broken commits.
I then optimized unit tests and made them two times faster.
I fixed false negatives in UI tests by rewriting them from Capybara to Cypress.
Microsoft System Center Operations Manager Additional Widgets Pack
http://social.technet.microsoft.com/wiki/contents/articles/24133.operations-manager-dashboard-widgets.aspxTool for Rapid Management Pack Prototyping Mokko MP
prototype a management pack to see how it will operate
without having to deploy it first. It involves no programming or an entire IT infrastructure.
It takes a few clicks to see and evaluate how the system center will monitor prototyped infrastructure and services.
Technologies used: .NET, C#, WPF, SCOM.
Education
Professional Degree in Radioelectronics
Tomsk State University of Control Systems and Radioelectronics - Tomsk, Russia
Certifications
Machine Learning Engineer
MADE Big Data Academy
Skills
Libraries/APIs
Sidekiq, EventMachine
Tools
Sublime Text, Terraform, Git, RSpec, Oh My Zsh, Celery, Ansible, Capistrano, Microsoft Silverlight
Languages
Python, Ruby, C#, JavaScript, C++/CLI, C++, Delphi, Go, Java
Storage
PostgreSQL, Microsoft SQL Server, Redis, Databases
Frameworks
Ruby on Rails (RoR), .NET, Windows Presentation Foundation (WPF)
Platforms
Docker, Kubernetes, MacOS, Heroku, Amazon Web Services (AWS)
Paradigms
High-performance Computing (HPC)
Other
Software Development, ActiveAdmin, ASDF, System Center Operations Management (SCOM), Algorithms, Data Structures, Machine Learning, Data Mining, Geospatial Analytics, Deep Learning, Big Data, Natural Language Processing (NLP), Graph Machine Learning, Speech Recognition, Generative Pre-trained Transformers (GPT)
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