The Data Leader’s Guide to Hiring and Team Building - Part 1

Hello all! This is Ben!

If you have missed some of my more recent articles, you might not be aware that I have started to write a book.

The prior chapter was broken into two articles:

• Don’t Lead a Data Team Before Reading This - The First Chapter

• Building Credibility As A Data Leader

The reason for this is because as I have talked with multiple data leaders over the past few years, I have often heard that they felt thrown into the position of leading a data team. I have also noticed that there remains a disconnect between the data teams and stakeholders.

In turn, I wanted to put together a book that helps cover key concepts for those looking to either lead a data team or be a more impactful senior-level engineer(and beyond). This book will cover everything from working with stakeholders, picking the right solutions, managing vendors, growing a team, and so on.

I want to give a very special thanks to Gordon Wong and Sebastyan Zaborowski for sharing your thoughts(If I missed someone, please do let me know and I’ll make sure to add you to the next one).

If you have led a data team, I’d also love to hear your stories and integrate them into this book.

Please feel free to reach out(you can respond to this newsletter)!

With that, let’s dive in.

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Now that you’ve started to get some answers to key questions for your CEO Rachel, it’s clear she’s ready to invest more resources into growing your team.

Rachel has been focused on elevating the business’s strategic use of data, and now she wants you to step up from being a data leader who gets stuck in the weeds to someone who can connect data initiatives more closely with business objectives. 

You realize, however, that there’s a missing piece—there isn’t much of a structured hiring process for your data team. You’ve been so caught up in the day-to-day technical work that planning for growth has taken a back seat. In fact, you’re not even sure where to start. Should you hire a data engineer, a data analyst, or a data scientist? While you know what each of these roles entails, you haven’t had the chance to determine which projects would benefit most from additional resources.

So, how do you begin building a team that not only executes but delivers results?

Regardless of how fancy your data stack is or how complex your workflows are, much of the success of your data team comes down to the people. Ensuring that your team is intentionally built and managed is a challenging task, especially if you’ve transitioned from an IC role into management. But it all starts with the hiring process.

The Hiring Pipeline

Hiring the right talent for your data team is crucial to making your data work for the business. It’s not just about finding someone with the right skills—it’s about finding the right fit for your team’s needs. And that’s always easier said than done. There are plenty of challenges when it comes to identifying the right candidates, whether you’re searching for data engineers, analysts, or simply figuring out which type of role should be prioritized.

That’s why I view hiring as a pipeline that starts long before you write up the first job requisition, and certainly doesn't end once you’ve sent the confirmation email. You need to create an environment where new hires not only want to work but can also see a clear path for growth and success. 

So, how do you go about hiring a data engineer, analyst, or scientist—and set them up to thrive? Let’s dive in. 

Hiring Starts by Creating a Great Environment