📈 📈 📈 Exciting news
Elementl has raised a $33M Series B to accelerate the growth of Dagster and Dagster Cloud! See the blog post
for more details. 📈 📈 📈
We’re really starting to see Dagster as oriented around data engineering as a craft and discipline.
This is a subtle yet important shift, as people often jump directly to the data engineer job title.
But it’s not just about data engineers. Lots of ML engineers and data scientists use Dagster, and it makes sense since ML engineering is mostly data engineering
. Analytics engineering is a data engineering subspecialty focused on sql-based analytics workflows. When they want to expand beyond that use case, or operationalize dbt in a broader data-engineering-driven platform, they bring in Dagster. Lots of you reading are also data platform engineers, whose job is to scale
data engineering across an organization, and think of all the other job titles above as your stakeholders. Our vision is that Dagster is the best place to build python-based data pipelines and the system that ties the work of all of you together in a single, coherent layer and control plane.
This capital will allow us to think bigger not just in terms of community and commercial growth, but also product expansion. In terms of realizing the potential of data engineering as a discipline, we are still in early days. Practitioners on the ground know there is so much more possible in terms of improving productivity and reducing chaos. We have an exciting roadmap ahead.
Thanks to all our users, community members, and Cloud customers. Your usage and support is what makes this all possible.
If you want to join us on this mission, we’re hiring across Sales, Marketing, Design, Operations, and Developer Relations. See our open roles here