A topic of discussion that comes up often is the ratio between the number of data engineers and data scientists. There is no good answer. It depends on the tools and infrastructure you have in place, the maturity of use cases for data and AI, and how you exactly define specific roles and titles.
With that said, the ratio of data scientists to data engineers may still be a useful indicator to gauge the level of engagement and maturity of a data team.
Here’s a quick aggregation of of data scientists to data engineers, in sectors that had at least ten companies as reported by Diffbot.
Software Companies: Microsoft reported the highest number of data scientist-to-data engineers, over 6:1.
Enterprise software companies: SAP had the highest ratio, over 14:1 data scientists to data engineers.
SaaS companies: Shopify reported 7:1 as the split.
Consumer service companies: Uber had the highest data scientists to data engineers ratio, over 8:1
Companies with well-regarded data teams have six or more data scientists per data engineer. While this seems like a reasonable ratio, the answer boils down to the tools and infrastructure you have in place, and the use cases.
With the emergence of low-code and no-code tools for data science and machine learning tasks, the ratio may very well rise soon.
