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Олександр
Junior Python Developer
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P Y T H O N D E V E L O P E R
[
https://t.me/AlexUzhva Enthusiastic and eager to learn. Multitasker, attentive to details, with
strong interpersonal and communication skills. I very like to be involved
[
ndr-uzhva-79a511304/ in everything that my team does. I like new challenges that make me
https://github.com/OleksandrUzhva want to learn more and more and motivate me to improve on a daily
basic.
SKILLS EXPERIENCE
Python Git JUNIOR PYTHON DEVELOPER
Django Docker TeamWise
Django REST Postman September 2023 - April 2024
PostgreSQL VS Code Responsibility:
FastAPI Notion
OOP Developed a web application for discovering and organizing
Multithreading online/offline events with map integration, chats, and user groups.
Multiprocessing Faced slow event filtering as the database grew; optimized SQL queries
Celery
using select_related and PostgreSQL indexes, improving performance by
SQL
Web scraping 3–4 times.
Google API Fixed incorrect map display of offline events by adding coordinate
validation and a fallback geocoding mechanism.
LANGUAGES
Resolved duplicate chat messages caused by unstable network
English - B2
conditions by implementing message_id checks and wrapping message
Ukrainian - native
Russian - C2 creation in database transactions.
Built a resilient event aggregator by adding fallback parsers and error
logging to handle inconsistent HTML from external websites.
EDUCATION
Technologies used: Technologies: Django, PostgreSQL, Git, web scraping,
ADDITIONAL COURSES
notifications.
Python Pro at Hillel IT School
2024 PYTHON DEVELOPER INTERN
MASTER DEGREE Awegoo
August 2024 - October 2024
Taras Shevchenko National
University of Kyiv Responsibilities:
2015-2016 Created automation workflows for data processing and
BACHELOR'S DEGREE integrations across Google Sheets, Python, and Notion.
Taras Shevchenko National Resolved Google OAuth2 authorization issues by configuring token
University of Kyiv storage and refreshing, ensuring stable gspread operations.
2011-2015 Encountered Amazon blocking and incomplete HTML responses;
implemented random User-Agents, delays, retry logic, and
response validation.
Cleaned and normalized noisy Amazon seller data using regular
expressions and custom parsing utilities.
Fixed errors when sending data to Notion by creating a data type
mapping system and adding pre-validation before API requests.
Improved overall script performance with batch operations and
caching of repeated computations.
Technologies used: Python, BeautifulSoup, requests, regex, Google
OAuth2, gspread, Notion API.
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