Backend-focused software engineer with 3+ years of professional experience designing and deploying scalable server-side systems. I specialise in Python (FastAPI, Django) with a strong emphasis on API performance optimization, database design and microservice architecture. I run production workloads on Google Cloud Platform and approach backend development with an engineering mindset — clear architecture, documented APIs and infrastructure that scales reliably under load.
Professional Experience
07.2023 — 12.2025 · 2 yrs 5 mos
Full Stack Web Developer
Waber Sp. z o.o.
- Created and maintained cloud functions in GCP Cloud Run, optimizing response times through asynchronous processing
- Optimized CRUD operations on Firebase Firestore, improving query performance with efficient data modeling and indexing
- Developed and maintained responsive web applications using Vue.js and Nuxt.js for multiple client projects
- Debugged and resolved performance bottlenecks across the full stack, reducing average page load time
Education
10.2021 — 02.2026
Bachelor's Degree, Computer Science
Lodz University of Technology
Field of Study: Computer ScienceSpecialization: Software Engineering
Highlighted Projects
Minsik
FeaturedA book discovery app built with a microservices architecture using Python and FastAPI. Backend designed as six gRPC microservices behind a REST gateway, with PostgreSQL storage, Elasticsearch full-text search, and Redis for caching and background jobs. Features JWT authentication, continuous data ingestion from Open Library and Google Books APIs, and a 9-dimension book rating system. Built the Nuxt.js frontend with SSR and SEO optimization. Containerized with Docker and deployed on VPS.
Ledger
FeaturedA production logging system built using a microservices architecture with Python and FastAPI. Processes over 10,000 logs per second, enabling teams to instantly detect application issues. Designed gRPC-communicating services with PostgreSQL for storage and Redis for caching. Implemented REST API for record querying and SSE for real-time error notifications. Applied horizontal scaling, async processing, and multi-layer caching. Containerized with Docker, deployed on VPS, tested with Pytest.