Vadim Ovcearenco

Massive multiplayer mobile project that involved many different disciplines like ultra low latency live streaming video, Elixir web sockets and a Django back-end for CRUD tasks and web views.

Role:
System Admin, DB Admin, Web Admin, Back-end Python and Elixir Developer

Technologies:
AWS, NGINX, MySQL, Python, Django, JavaScript, Elixir, Phoenix

Challenges:
We used Elixir/Phoenix to create web socket channels with clients. It gave us best performance and almost no latency.

Prymesyft is software house specialized in web applications. They needed the app to control contracts, payments, project progress and tasks management for the client.

Role:
Full-stack Developer

Technologies:
AWS, EC2, RDS, Python, Flask, SqlAlchemy, AngularJS

Challenges:
Find the best AngularJS architecture to provide easy development and updates.

The application to archive email/web data of a client, where the client can create account on the web app and set up what site and what mails he/she wants to archive, and as for the tech stack the folowwing is used, Python, Django, Docker, Amazon SQS, Amazon SNS, Vue.js, Postgres, Elasticsearch.

Role:
Full-stack Developer. I was responsible for email archiving.
All incoming emails should be parsed, inserted in DB and search engine (Elasticsearch).

Challenges:
Create a robust workflow for email processing. User permission access, Effective archive search and management.

Description:
Collecting, processing and analyzing skin photos using AWS. The company previously had the project running on GCP.

Role:
As most of the code was written for GCP (by me), I had to migrate to AWS using AWS tools.

Technologies:
EC2, Elastic Beanstalk, Elastic Container Service, Lambda, Auto Scaling, Docker, S3, RDS, SQS, SNS, CloudWatch. CodeCommit, Flask, Ubuntu, JavaScript

Challenges:
Find the best tools in AWS to optimize performance vs. cost. Improve the error handling flow.

Description:
Collecting, processing and analyzing skin photos using Google Cloud Platform (GCP)

Role:
I had to design software and hardware architecture to create an API REST interface for the mobile client, to create a minimum-functionality web client using JavaScript libs.
The system should be able to process 6000 photos per hour.

Technologies:
BigQuery, Storage, Datastore, Kubernetes, Google Logging, Compute Engine, Queues, Flask, Ubuntu, JavaScript

Challenges:
To provide required performance, we used Google Container Auto-scaling. All errors are saved in a special queue for processing manually later. The analyzer was run every day and computed all statistical data.

Q&A education application.

Flask, PostgreSQL, SQLAlchemy

Copy log from AWS to Google Cloud and filter it.

Google App Engine, Google Storage, Python, AWS, S3

Organize ADF workflow.

Google App Engine, Google Pub Sub, Google Big Data, Python

Kiwi.com is a web platform for airline ticket booking. I worked as a back-end developer and was a member of the fintech department.

As a senior software engineer, I implemented the payment module using card payments, Apple payments, and others. The main focus was on system reliability and error handling. My team used an advanced monitoring tool (Datadog) and reports to track all payments.