Tomas Ripsky · portfolio

Data Engineering Lab

Projects built end to end — ingestion, cloud infrastructure, modelling, tests, CI/CD and a public site — to learn the craft in the open. Each one answers a question for readers who don't know its domain, and each has its own look.

pitwall

How are Formula 1 races won with tyres and pit stops?

Every race since 2023, refreshed each Monday after a Grand Prix: strategies, tyre wear and the undercut, explained for people who don't follow F1.

OpenF1 · Python · GCS · BigQuery · dbt · Terraform · GitHub Actions · Observable

Open the dashboard →

CityPulse

Does the weather change how New York rides bikes?

Twelve months of weather and air quality against 44.5 million Citi Bike trips: rain, snow, wind and heat measured against a normal day.

Open-Meteo · Citi Bike · Python · GCS · BigQuery · dbt · Airflow · Terraform · Observable

Open the story →

MarineFlow

Where is every ship right now, and which ones behave oddly?

The live AIS feed of vessel positions monitored within seconds, then turned into hourly analytics: port traffic, behaviour detectors and a risk score.

AIS · Kafka · Spark Structured Streaming · GCS · BigQuery · dbt · Airflow · Grafana

Open the project site →

How these are built

Every project lives in its own repository and starts from the same base: the data-engineering-lab repository, which holds the rules all of them follow (conventions, security and cost guardrails, decision records), the project template, and the operating manual of the AI teammate — Claude Code — that designs, builds and explains each one with me.

Source code: pitwall · CityPulse · MarineFlow · the lab