Position: Python Lead Developer
Category: Python
English level: pre
Years of experience: 4


Objective:
Seeking a challenging role in software development where I can leverage my expertise in backend development, database design, data processing, and trading terminal development to contribute to the success of innovative projects.

Professional Experience:

Onlihub Startup 
Role: Lead Developer

Took on the responsibilities of designing the database structure and overall project architecture after the lead developer had to leave the project due to family circumstances.
Specialized in backend development, focusing on building a robust asynchronous API with multi-threaded processing and queue management using FastAPI.
Developed complex SQL queries for PostgreSQL, including dynamic queries and optimized query performance for handling large datasets.
Proficient in data processing and visualization using PowerBI.
Created numerous integrations with various warehouses and marketplaces, including eBay, Etsy, Amazon, Zenventory, Ysell, and Onedaybundle.
Developed various parsers that account for blocking, multi-account usage, and different proxies.
Designed a tool for managing recurring tasks.
Demonstrated expertise in software design patterns and adherence to coding best practices.
Proficient in using tools and libraries such as Selenium, BeautifulSoup (bs4), Requests, Scrapy, Multiprocessing, Multithreading, asyncio, and FastAPI.
Maintained and documented API methods to ensure clarity and ease of use.
Trading Terminal Development:

Designed and developed a trading terminal with a graphical user interface using PyQt5.
Implemented features for retrieving cryptocurrency price data from exchanges and visualizing charts.
Integrated common technical indicators such as Moving Averages (SMA, EMA), MACD, TMA, RSI, etc., for technical analysis.
Simulated historical market behavior to enable backtesting of trading strategies.
Enabled users to create and test their own trading strategies within the terminal.
Supported live trading by connecting to cryptocurrency exchanges and executing trades based on predefined strategies.
Recorded and displayed all executed trades on the chart.
Implemented commission calculations to provide accurate profit and loss calculations.
Offered the capability to save trading results to a file for analysis.
Utilized libraries such as yfinance, pandas, numpy, matplotlib, and numba for efficient data processing and visualization.
Implemented multi-threading for parallel task execution using QThread and Thread.

_vangardo