Why I’m Studying Data Engineering

📌 From Marketing Data to Data Engineering: Why I’m Taking the Next Step

For the past few years, I’ve worked at the intersection of marketing, automation, and analytics—building systems that help track performance, connect platforms, and surface insights.

Over time, I’ve found myself pulled more and more into the technical side of that work: writing Python scripts, designing data flows, building pipelines into BigQuery, and integrating tools like our CRM with cloud-based automations.

Somewhere along the way, it stopped being just marketing ops and started feeling like data engineering in disguise.

So I’ve decided to formalize what I’ve already been doing by pursuing the Google Cloud Professional Data Engineer certification. The goal isn’t just the credential—it’s to solidify the foundation I’ve already been building, explore best practices, and grow into more complex and scalable systems.

I’ll be documenting that process here—not as a tutorial site or a polished portfolio—but as a place to reflect, clarify my thinking, and practice communicating technical concepts as I learn them.

I’m excited to sharpen these skills and build more structure around the work I’ve been doing lately. If you’re on a similar path—or just interested in how marketing data becomes something much more—I hope you’ll follow along.