Data Engineering Case Studies
Real companies. Real problems. Here's how we solved them.
Who We Work With
Most of our clients come to us at the same point: the company is growing, data lives in too many places, and the person who's been holding it all together can't keep up anymore. They don't need a $300K full-time hire. They need someone who's done this before and can get it right the first time.
We work with companies between 10 and 200 people who are at exactly that moment.
Building a dbt Data Foundation from Scratch: A Case Study for Startups Without a Data Team
Health tech · ~50 employees · No data person, just a CEO, AI, and a lot of manual checks. Now 12 people rely on the same infrastructure.
Building a Self-Serve Analytics Culture with Metabase: A Case Study for Startups Without a Data Team
Health tech · ~50 employees · 11 non-technical users now making decisions from data, without asking anyone for help
Building an AWS Event Tracking Pipeline from Scratch: A SaaS Case Study
Flexible office marketplace SaaS · ~150 employees · Fast-growing, investment-backed · Full Pentaho to AWS migration
Replacing a Legacy ETL Tool with AWS: A SaaS Migration Case Study
Flexible office marketplace SaaS · ~150 employees · Fast-growing, investment-backed · Full Pentaho to AWS migration
Building a Data Lakehouse from Scratch on AWS: A Case Study for Complex Organizations
Multinational organization · ~500 employees · $32M revenue · No prior data infrastructure
Want the how-to behind these builds? Read the data engineering blog.
Working with a similar challenge?
Book a free 1-hour data strategy call and we'll tell you exactly what we'd build and why.