Position: Big Data Engineer
Category: Python
English level: fluent
Years of experience: 3

- project to parse Amazon data using Tor network of free proxies as an alternative to paid services (client could decrease monthly costs by a few thousand US dollars)

- background before switching to IT - economics & finance (passed 2 out of 3 levels of Chartered Financial Analyst [CFA] qualification), data analytics roles in various Ukraine-based western-capital top-tier banks / investment & insurance companies.
- 4th commercial project (~6 months) - global privacy protection-based search engine (DuckDuckGo alternative). I defined architecture and built integrated and automated parsing of Wikipedia articles big data dumps within AWS Serverless infrastructure (AWS Step Functions, Lambda, Glue/PySpark, DynamoDB, AWS SAM) - to use it for displaying Wikipedia widget in a search engine results.

- 3rd commercial project (~3 months) - NFT-market based project in transition from Flask to Django. Writing basic Django replica (basic fullstack Django/Bootstrap) app from scratch with functionality of existing project in Flask (using docker & docker compose, consisting of Django web app, nginx, celery, Postgres, Redis, Rabbitmq), celery jobs of parsing of data from Opensea, endpoints and views, user dashboards & authentication etc.) 

- 2nd commercial project (~14 months) - US e-commerce platform for managing products marketing on Amazon - new functionality, performance & speed improvements, debugging, Pytest tests from scratch, ad hoc scripts.

- 1st commercial project (~7 months) - US e-commerce platform for managing logistics & goods deliveries costs & efficiency for e-commerce traders - improvements and debugging.

- pet-project (~6 months) - e-commerce platform for managing drop-shipping products sales in Ukraine - myself full-stack building from scratch to MVP.
Focus on back-end.

However, I have some practical experience with integrating back-end with HTML / Bootstrap / CSS / Javascript / JQuery / Ajax / Jinja.