We started Clean Bad Data because we spent 40% of our time fixing broken datasets. We built the tool we needed.
Clean Bad Data was founded in 2022 by Maya Chen and Daniel Ortega — two data engineers who met at a Fortune 500 company where they spent more time fixing CSV exports and debugging schema mismatches than building data products.
They built the first version of Clean Bad Data over a weekend hackathon. Within three months, their former employer had adopted it company-wide. Today, over 600 data teams use Clean Bad Data to process more than 4.2 billion rows every month with 99.7% validation accuracy.
We are a team of 28, fully remote, headquartered in San Francisco with team members across 8 countries. We are backed by trusted VCs but remain fiercely independent in our product vision.
