Building a data team from scratch

Building a data team from scratch

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The Journey to Building a Data Team

Before we get into the nuts and bolts of building a data team, I think it’s worth sharing how I got here. Right now, I’m the Business Data Analyst Team Lead at Signable, where I’ve been for five and a half years. But back in 2018, I was fresh out of uni, stepping into Signable with a marketing degree and a lot of curiosity. I started as a Marketing Executive, which meant running Google Ads, using Google Analytics (the old UA days, pre-GA4), and, eventually, getting into Google Tag Manager and Data Studio. Those early projects were my first real dive into data analysis, and I quickly saw how powerful data could be in decision-making.

But, as I was digging into Google Ads – tweaking keywords, tracking campaigns, and looking at click-through rates – I noticed a gap. We knew how many trials were coming in, but we had no way to measure return on ad spend (ROAS). I started asking questions, but the development team was knee-deep in product work, and the marketing team didn’t have a clear answer either. That’s when I was given a chance to tackle it myself, and I jumped right in. Within a few months, I’d fully transitioned into data analysis and became Signable’s first full-time data team member.

Step One: putting out fires & showing value

One of the first things that helped me was having a mentor. I was lucky enough to work directly with Olly Culverhouse, Signable’s CEO. In those days, Signable was small and had a flat structure, so I reported directly to Olly for the first few years. It was a game-changer for me. Olly had the technical background to point me toward the right tools but also gave me space to find my own solutions. That mix helped me build up critical thinking skills and self-sufficiency – two things I couldn’t have done without in a team of one!

If you’re just starting out and can find a mentor who understands both the business and the technical side, take full advantage. It pushed me to think fast and problem-solve on the fly, knowing I had someone who understood the challenges.

Key takeaway:

  • A mentor with technical know-how is a huge asset, especially when you’re just getting started. They’ll push you to find solutions independently while giving you a solid support system.

Step Two: starting from the bottom

In the beginning, my skill set was fairly basic – Google Ads, Google Analytics, Search Console, and Data Studio. My reports pulled together campaign data, search intent insights, and the occasional CSV file for good measure. These were early days, and my main focus was answering marketing’s biggest questions. But those projects? They were exciting and really motivated me to keep learning.

I started looking around for ways to level up and stumbled across a Python course on YouTube, designed specifically for marketers. That’s where I got my first taste of coding, and I was hooked. Those early projects taught me that working with the tools you already have is better than waiting around for new skills to magically appear. Looking back, some of my first reports might seem a bit rough, but they did the job and helped me show the business the value of data.

Key takeaway:

  • Work with what you’ve got! Those early wins – even if they’re basic – are what drive influence and push you to learn more.

Step 3: skill up while doing your job

Once I’d worked through the YouTube course, I signed up for an online course to dive deeper into SQL and Python. The best part? Everything I was learning, I could use right away. With new skills, I expanded beyond marketing data, creating reports for sales, customer success, and other teams.

It felt like I was constantly running around, putting out fires across departments. But each time I tackled a new issue, I showed the value of data in a tangible way. And, with each new report, I gathered more “data cheerleaders”  – people across the business who saw firsthand how data made their lives easier and started advocating for it.

Key takeaway:

  • Find your “data cheerleaders” in the company. These advocates help others see the value of data and create a ripple effect of influence.

From marketing data to company-wide impact

My role evolved from creating campaign reports for marketing to handling data needs across the entire business. I went from building marketing reports to creating KPI trackers for heads of departments, dashboards for customer success, and product performance reports. Each project helped me demonstrate the impact of data, setting the foundation for a company-wide data strategy. And now? Data has become a critical part of decision-making at Signable, driving improvements in efficiency, customer satisfaction, and product development.

Building a data team from scratch has been no small feat, but by focusing on showing value, connecting with the right people, and staying curious, you can position yourself for long-term success. In the next piece, I’ll dive into the next phase: evolving the tech stack, developing a data strategy, and scaling your team as your company continues to grow.


Ready to see how data-driven insights can transform your business? At Signable, we’re constantly learning, growing, and creating smarter ways to work. Learn more about how our electronic signature solution can help streamline your processes, make data-informed decisions, and scale with ease. Explore Signable today.

MJ sat at a desk with laptop in front of him smiling directly at the camera
Marijn (MJ) Quartel
Business Data Analyst Team Lead

Marijn (MJ) is a Business Data Analyst Team Lead with an extensive background in marketing. Leading the Data Team at Signable, he is responsible for a variety of projects involving Product, Customer, and Marketing data. Identifying a need for thorough data analysis at Signable, MJ independently mastered a wide range of skills, including SQL, Python, and various analytics tools. When not knees deep in a query, he likes to collect Pokemon cards with his sons, boulder, or listen to audiobooks. For insight into his latest projects, or questions on data, connect with MJ on Linkedin.