Scaling Data Engineering in the Age of AI

By Matthew Scullion, CEO and Co-Founder, Matillion

AI is reshaping how organizations use data and revolutionizing how data teams work. In this series, Matillion’s executives share their perspectives on what it will take to lead in the AI era. 

From unlocking new revenue streams, to accelerating innovation cycles, to turning data into a competitive advantage, these are pragmatic insights from leaders building the future of data-driven business.

Data engineering has always been both a creative and highly skilled discipline, but also one where enterprise teams constantly feel stretched thin. Research shows that 80% of enterprise data teams feel “underwater,” struggling to keep pace with the demand for data.

The rise of AI is only accelerating this pressure. Today’s organizations already run on dozens or even hundreds of AI agents. Soon, there will be thousands. Each will need timely, accurate data to operate effectively. That means an exponential increase in data engineering workloads.

You can try to meet that demand by scaling human teams, but it’s slow, expensive, and still limited by headcount. Or you can rethink the model entirely.

That’s why we built Maia, an agentic data engineering team inside Matillion’s Data Productivity Cloud. Maia is more than a Copilot; it is a set of AI-driven personas and capabilities that can design, build, and modify pipelines, handle repetitive tasks, and deliver complete, production-ready workflows.

This changes the role of the human data engineer. Instead of being limited to what one person can deliver, each engineer becomes a leader with a team of AI data professionals working alongside them. Routine changes, like pulling a new field from source to destination, can happen in minutes. Entire pipelines can be designed and deployed from a high-level request.

As AI adoption accelerates, the volume and variety of data pipelines will grow dramatically. Without the ability to scale productivity, organizations risk slowing their AI initiatives and losing ground to competitors that can move faster. By making each engineer five, ten, or even one hundred times more productive, Maia enables a truly limitless approach to data engineering.

In the next era of business, speed and scale will decide the winners. With Maia, your data team has both.

See Maia in action.