Python Developer — Automation, Bots & Data Pipelines

For the past five years I have used Python to take repetitive, error-prone work off people's plates and turn it into something that just runs on its own. If a task involves moving data between systems, watching an API, generating the same report every morning, or answering messages in Telegram, there is a very good chance I can automate it for you. I treat automation as a product rather than a throwaway script: it should log what it does, recover gracefully when something goes wrong, and be easy to hand back to your team.

My work spans a few connected areas. I write bots on aiogram 3 with proper state handling, payments, and admin controls; I build web scrapers with Scrapy, Selenium, and Playwright that survive real-world sites and rotate proxies; and I design data pipelines that pull, clean, and load information on a schedule so your reports are always current. When you need a proper backend behind all of this, I build async APIs on FastAPI with authentication and generated documentation. Everything ships in a form you can actually run — containerized, tested, and deployed.

Tell me what eats your time, and I will tell you honestly whether Python is the right tool for it and how I would approach the build.

— Automation scripts: file processing, API polling, report generation
— Telegram bots: aiogram 3, FSM, payments, admin panels
— Web scrapers: Scrapy, Selenium, Playwright, proxy rotation
— Data pipelines: pandas, ETL, PostgreSQL, scheduled jobs
— FastAPI backends: REST APIs, async, JWT auth, OpenAPI docs
— Browser automation: Playwright testing, form filling, data extraction
— Stack: Python 3.11+, asyncio, FastAPI, SQLAlchemy, pydantic, PostgreSQL, Redis, MongoDB, Docker, GitHub Actions