Organizing separate data engineering teams to develop and own data pipelines and products — separate from the stream-aligned business domains they serve — is an antipattern that leads to inefficiencies and weak business outcomes. This structure repeats past mistakes of isolating DevOps, testing or deployment functions, creating knowledge silos, bottlenecks and wasted effort. Without close collaboration, data engineers often lack the business and domain context needed to design meaningful data products, limiting both adoption and value. In contrast, data platform teams should focus on maintaining the shared infrastructure, while cross-functional business teams build and own their data products, following data mesh principles. We put this practice in Hold to strongly discourage siloed organizational patterns — especially as the need for domain-rich, AI-ready data continues to grow.
