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Nazar
Data engineer
Контактна інформація
Шукач вказав телефон , ел. пошту та LinkedIn.
Прізвище, контакти та світлина доступні тільки для зареєстрованих роботодавців. Щоб отримати доступ до особистих даних кандидатів, увійдіть як роботодавець або зареєструйтеся.
Отримати контакти цього кандидата можна на сторінці https://www.work.ua/resumes/15117001/
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DATA ENGINEER
Lodz, 93-590, Poland | [
PROFILE
Github: https://github.com/softkK1T
Telegram: https://t.me/ytbko
Data Engineer with 2 years of hands-on work building daily data pipelines for ecommerce, moving product data
from websites into PostgreSQL reliably and on schedule.
Focused on clean, consistent data: standardizing different sources, checking completeness with SQL, and quickly
resolving issues with alerts and monitoring.
Tech: Python, Airflow, S3, PostgreSQL, Docker, GCP/AWS;
Based in £6dz, open to junior data engineering roles.
PROFESSIONAL EXPERIENCE
Career Development Break 05/2024 — Present
* Pursuing Bachelor's degree in Informatics (part-time)
* Building production-ready data engineering projects (Djinni Analytics, Crawler API, Pasta Pipeline)
* Deepening expertise in Apache Airflow, ETL pipelines, and cloud infrastructure
* Transitioning from web scraping to comprehensive data engineering solutions
Data Engineer, Profitero, Lodz 05/2022 — 05/2024
Wrote and ran web scrapers in Ruby (Chrome emulator, curl-impersonate). Daily/weekly runs, saved data as JSON/CSV to
PostgreSQL. Created and maintained scrapers for 30+ e-commerce domains across multiple locales, handling CAPTCHAs
and using mobile device emulation to get needed API endpoints when desktop version doesn't allow it. Implemented core
scraping logic: pagination, category traversal, variants, and price/availability parsing; updated selectors when sites changed.
Added alerts to notify on blocked or failed runs. Kept outputs in the correct format (consistent fields/types) so downstream
use stayed simple.
SKILLS
Python, Ruby SQL, PostgreSQL Em Apache Airflow
AWS S3, GCP Storage Git, Docker, Redis, Celery,
FastAPI|
PROJECTS
Djinni Job Market Analytics Platform 08/2025 — Present
Built an automated ETL pipeline using Apache Airflow to collect and analyze job postings from djinni.co. The system extracts
vacancy data including salaries, required skills, and company information, storing everything in PostgreSQL. Implemented
a modular architecture with separate Extract, Transform, and Load stages, integrated external Crawler-API to bypass
anti-scraping protection, and added batch processing with automatic retry mechanisms. Used BeautifulSoup4 and XPath
for HTML parsing, Redis as Celery broker, and containerized the entire infrastructure with Docker.
Technologies: Python, Apache Airflow, PostgreSQL, Redis, Docker, BeautifulSoup4, Ixml
Git: https://github.com/softK1T/djinni
Crawler Microservice 11/2025 — 11/2025
Developed a high-performance web scraping microservice with REST API endpoints for single and batch URL crawling.
Implemented intelligent proxy pool management featuring automatic rotation, blocking detection, and performance statistics
tracking. The service handles asynchronous task processing through Celery, includes error handling with retry logic, supports
HTTP/2 protocol, and provides health check endpoints. Built with FastAPI for the API layer, Redis for caching and task
brokering, and httpx as the HTTP client. Fully containerized using Docker.
Technologies: Python, FastAPI, Celery, Redis, httpx, Docker
Git: https://github.com/softkK1T/crawler-api
Pasta Vault - Telegram/HTML content scraper 05/2025 — Present
Developed an automated ETL pipeline using Apache Airflow to extract and process content from Telegram channels.
The system scrapes messages via Telegram API using Telethon, extracts Telegraph article links, and fetches full content
asynchronously with aiohttp. Implemented four processing modes (incremental, refresh, daily, full) for flexible data collection,
batch processing with configurable sizes, and duplicate removal logic. Built error handling with retry mechanisms, rate
limiting, and timeout management. The pipeline stores structured data in PostgreSQL. Containerized with Docker.
Technologies: Python, Apache Airflow, PostgreSQL, Telethon, aiohttp, Beautifulsoup4, Docker, Prometheus
Git: https://github.com/softK1T/pasta-pipeline
EDUCATION
Informatics 10/2024 — Present
Academy of Social Sciences, £6dz
Focused on algorithms, data structures, and software engineering fundamentals.
ADDITIONAL INFORMATION
* Languages: English, Polish, Ukrainian, Russian
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