With a focus on building scalable systems and driving real-time performance, Brett Ulrich serves as SVP of Engineering at DMS. Known for combining technical depth with a strong sense of business impact, Brett leads engineering efforts that power DMS’s data-driven infrastructure and enable high-intent customer acquisition.
In this Q&A, Brett shares insights into the complexities of real-time data, the systems behind performance marketing at scale and what it takes to build technology that consistently delivers measurable results.
Q: Performance marketing runs on speed, data and constant optimization. How do you think about building systems that can keep up with that pace without breaking?A: There are three major bottlenecks in high-performance systems. We look to optimize all of these.
First, input systems and response times. We operate in a high-throughput IO environment that few businesses experience. To manage the scale, we use different strategies at the edge of the network and monitor integrations to ensure we can always accept traffic.
Second, our internal market-making system requires that we understand the microstructures of our lead pricing and sales orders. We use efficient programming languages, auto-scaling architectures and hot-path strategies to match the right buyers with the right leads at the right time.
Lastly, our data persistence layers are designed to move data away from transactional systems as soon as possible. With petabytes of data under management, our servers are constantly working to move, refine and summarize data for reporting systems and APIs.
Q: What are some of the biggest technical challenges teams face when working with real-time data and high-intent consumer interactions, and how do you approach solving them?
A: Since we depend on data from multiple sources (e.g., ad platforms, publishers, affiliates) in different shapes and sizes, the challenge is getting that data cleaned and connected to the sales pipeline analytics in real time. Leveraging modern replication systems, machine learning and data warehousing, we can often link high-intent customers to the right buyers within minutes.
Q: How do you ensure the systems your team builds actually translate into better performance and outcomes for clients?
A: We have built and launched proactive notifications on hundreds of metrics. It is part of the engineering ethos at DMS that business quality metrics are our responsibility. The team is constantly asking, “How does today compare to yesterday, seven days ago, thirty days ago?” Proactive Slack notifications keep us alert for anomalies that could represent missed opportunities for customers and clients.
We experiment and improve our metrics by focusing on lead quality, setting up new data integrations, historical research projects and backtesting on rule changes. Our latest experiments include instilling AI agents to highlight the next generation of opportunities to serve our customers.
Q: As SVP of Engineering, what does leading a successful engineering team in a performance marketing business like DMS mean to you?
A: The mindset that makes the difference on a performance marketing engineering team is a clear vision of how we deliver solutions to customers. “I wrote the code” is not enough to be successful. We need to get our optimizations into customers' hands as quickly as possible.
Also, software engineering is a team sport. To pull an analogy from the game of hockey, the best players know where the puck is going and put themselves in that position. Our teams perform best when we can keep the DMS vision in view and have the sensitivity to reduce friction for our teammates before they get stuck.
Q: When you’re not focused on engineering and building systems, how do you like to spend your time?
A: Outside of work, I like to keep things pretty balanced. I enjoy spending time with my family, being outdoors, cooking great meals, working on projects around the house and building video games with my daughter. I also genuinely enjoy learning, so I tend to spend time reading about business, technology and investing.
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