Why you (yes you) should consider joining the dbt Labs marketing team

Growth: 3x growth year-over-year for five years

The north star metric we use for dbt is Weekly Active Projects. This represents the total number of companies running dbt in production each week. We’ve been tracking this number since 2016 and dbt adoption has has been growing 3x year-over-year for the past five years.

from our Series C announcement

Market Size: Enterprise data management market growing from $77.9B in 2020 to $122.9B in 2025


Customer Satisfaction: See for yourself in the 17k+ person dbt Community Slack

dbt is a fast-growing product in an exploding market. But…is the product any good? If you’re a marketer, it’s unlikely that you’ll be able to just jump into the product and evaluate it yourself. But there is plenty of information out there to help you get a feel for just how much people love dbt.

  1. If you know any analysts or data people, ask them if they’ve heard of dbt and what they think. They probably have. And if they haven’t, show them them the website and see if dbt messaging resonates.
  2. Poke around in the dbt Community. It’s fairly common for open source products to have some type of developer community grow around them. What’s unique in the case of dbt is that dbt, and the analytics engineering workflow, are evolving in this new “cloud data platform” world. AND dbt introduces a whole new group of users (analysts) to what are established software engineering best practices like version control, testing, documentation, modularity, CI/CD. This makes the dbt Community uniquely valuable as a space for learning and building together. The best way to explore the dbt Community is to join the dbt Community Slack or attend a dbt Meetup.
  3. Search Twitter and see what our users are saying (pro tip: use “dbt+data” to filter out the Dialectical Behavior Therapy tweets)
  4. Search LinkedIn and see what our users are saying (again, use “dbt+data”)
  5. Search Medium and see what our users are saying (again, use “dbt+data”)
  6. Read our case studies, Jetblue and HubSpot are good starting points
Reactions in dbt Community Slack to our Series C announcement and name change from Fishtown Analytics to dbt Labs

Founders: The best possible people to solve this problem

Products in the data space tend to be built for data engineers or business people. Tooling built for data engineers is robust and scalable but suffers from inaccessibility, which slows data teams down. And tooling built for business users has a low barrier to entry but suffers from good governance, which ultimately fails to scale and slows data teams down.

Convinced yet?

There is a lot of good stuff happening at this company. There is a lot of good stuff happening in this industry.



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