Data and product to engineer ratio at 50 tech scaleups

Diving into data for 50 tech companies about the number of people in data, engineering and product roles reveals interesting patterns about how they operate.

We’ve used publicly available data from LinkedIn on tens of thousands of profiles to examine how many people are in data, engineering and product roles. We’ve used the following job titles to group profiles

Data: Data analyst, data scientist, machine learning engineer, data engineer, product analyst, business intelligence, data warehouse, analytics engineer, data manager, data lead, head of data, data director, vp of data, chief data officer
Engineering: Engineer/engineering (all matches but excluding data engineer), developer, tech/technical lead, chief technical officer
Product: Product manager, product lead, head of product, director of product, vp of product, chief product officer

We also look into the data, engineering and product teams relative to the overall company size. A few companies such as Instacart, Doordash and Remote have many profiles listed in operational and contractor roles which make the overall company size harder to compare to their peers.

Data and product to engineering ratio

For the companies in the sample, the median data to engineer ratio is 0.13x and the median product to engineer ratio is 0.12x. While it’s more common to have a slightly a larger data team relative to the product team, there are also companies where the product team outnumber the data team.

The companies can be grouped into data first, product first and engineering first.

Data first: Data led companies have large data teams relative to the engineering team. These companies typically have business models where data directly contributes to the bottom line such as Tinder, Doordash and Instacart that all use data as a core part of their business model and operations.

Product first: Some companies such as Personio, checkout.com and Cover Genius have relatively larger product teams. There’s not one factor that determines why this is the case. Cover Genius for example have a handful of people employed with the “Insurance Product Manager” title.

Engineer first: These are predominantly platform and development heavy companies such as Rippling, GitLab and GitHub. In many cases they have engineers carry out part of the job that overlaps with what the product and data team would normally do.

Engineering to data and product ratio

If we flip the ratio around and look at the number of engineers relative to the data and product team it’s clear that companies such as GitHub, Webflow and GitLab heavily outnumber other companies with more than 15 engineers per product and data person.

Looking at the stats for data, product and engineering teams relative to the total number of employees gives another perspective. There are a few caveats with the data such as Doordash, Instacart and Remote having many contractor workers making the total number of employees much higher and skewing comparisons.

Data team relative to overall company size

The data team size relative to overall company size ranges from 1% to 5%. The list is topped by well known B2C and B2B brands such as Loom, Faire and Typeform.

Product team relative to overall company size

The product team relative to total company size also falls within the 1% to 5% range.

Engineering team relative to overall company size

With 37% of employees in engineering roles GitHub comes out top of the list. Companies with the relatively smallest engineering teams have around 12% of total employees in engineering roles.