Why Data Teams Keep Reinventing the Wheel: The Struggle for Code Reuse in the Data Transformation La

Data teams have a bad habit: reinventing the wheel. Despite the explosion of open-source tooling, best practices, and managed services, teams still find themselves building bespoke data platforms from scratch—often hitting the same roadblocks as those before them. Why does this keep happening, and more importantly, how can we break the cycle?

In this talk, we’ll unpack the key reasons data teams default to building rather than adopting, from technical nuances to cultural and organizational dynamics. We’ll discuss why fragmentation in the modern data stack, the pressure to “own” infrastructure, and the allure of in-house solutions make this problem so persistent.

Using real-world examples, we’ll explore strategies to help data teams focus on delivering business value rather than endlessly rebuilding foundational infrastructure. Whether you’re an engineer, a data leader, or an open-source contributor, this session will provide insights into navigating the build-vs-buy tradeoff more effectively.