How to Structure Your Team When Building a Data Startup

How to Structure Your Team When Building a Data Startup

How to Structure Your Team When Building a Data Startup

Data Startup in mind? Need to structure different teams? Here are guidelines for structuring Data Team, Crawl Development Team, Data Infrastructure Team, and more.

How often do you get advice that is directly relevant to what you need right now? Probably never.

As a startup founder, I read a lot of articles about building and growing a business. A lot of these articles have great advice, but often try to reach a broad audience, and therefore end up glossing over the details that can really matter.

It’s possible I can make a small dent in that problem by providing some insight into the specifics of building a data startup. If you’re responsible for a data startup yourself, or any team involved in operating big data-scale technology, then this article (and others to follow) can serve as a guide for how to build and run that team. I don’t promise to have all the answers, but I can share what I’ve learned over the last few years building Datafiniti. Hopefully you’ll find the material helpful, and just a bit more relevant to your needs right now.

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I’ll start by laying out our current team structure at Datafiniti. Our “org chart”, if you will:

Here’s what each of these mean:

This team layout roughly follows Jeff Bezos’ 2-Pizza Rule for team sizes. Following this principle wasn’t my intention, but I have observed better team communication and cohesiveness since we adopted this layout. As the team grows, my current plan is to split out new teams whenever an existing team gets larger than six people in size.

 



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