Rafał – Python, Django, PostgreSQL

It is a feature in a platform for commercial airplane route planning which shows live data of all aircraft on the map, such as position, altitude, heading, pressure, speed, etc.

• Designed high-performance architecture for processing around 5000 complex data points per second;
• Implemented data retention;
• Carried out cache handling;
• Prepared deployments;
• Implemented parsing into pydantic data models;
• Performed monitoring of multiple metrics and presented them on dashboards along with alerting system.

It is a Slack-like messaging app allowing communication between pilots and airline dispatchers without using complicated protocols and machines.

• Designed crucial parts of the back-end in microservices-based architecture;
• Built and implemented REST API endpoints for direct front-end usage;
• Integrated back-end with Firestore;
• Created Grafana dashboards for monitoring many parts of the solution.

It is a complex processor for Notice To Airmen (NOTAM) - messages sent to pilots. It filters and parses messages, performs database operations, and publishes events across many systems.

• Implemented parsing and database operations ;
• Carried out and deployed workers;
• Implemented monitoring of multiple metrics like errors, types of data, and load, along with alerts;
• Developed endpoints for gathering NOTAMs;
• Wrote unit tests.

It is the main tool for analysts in Financial Crime Unit used for managing the Know Your Customer procedure - a complex process which results in a decision if a company should start a relationship with a given client.

• Designed and implemented the whole back-end;
• Created database models and optimized queries;
• Prepared separate Docker containers for FastAPI and MSSQL deployments;
• Implemented several REST endpoints for data gathering and data transformations.

It is an app that reviews the picture of a wrecked car and immediately knows not only what's been damaged but also tells what would be the cost of repair, having a Machine Learning model.

• Implemented REST API as an interface for asking the model along with data streaming and image preprocessing with NumPy and OpenCV;
• Prepared Dockerfiles with multistage builds;
• Implemented all needed CRUD operations.