Hi,

Over the years, I have noticed that many series A, and in particular seed, startups do not have a data engineer/analyst/generalist on payroll. This data role seem to be an oversight or a luxury that isn't invested in until they reach a series B sort of level. Which, by this stage, the data can be an absolute mess.

I get that for some businesses it might not be applicable to have skilled workers like this at all. But almost every VC funded business will need to be compiling periodic metrics to share with their investors - which can take hours and hours in Excel, which is the defacto solution for pretty much everyone.

Plus, getting early insights into the business (i.e. making data driven decisions) can help lower costs, improve conversions or help scale the business quicker - which is very hard without a proper data stack being setup and put on autopilot.

So my questions are:

1. If you are a seed or series A startup who has not hired a data engineer (who is a data generalist), why haven't you (e.g. no need, happy to spend hours a month doing this in Excel, don't have the funding capacity yet etc)?

2. If you have hired a data generalist, why did you decide to hire this skill set and have you seen the benefit of hiring them?

Hopefully that makes sense :)