In This Issue of the Data pro News, we look at an excerpt from "The Data Engineering Mandate for 2026," outlines the critical transformation facing data engineering professionals as Artificial Intelligence matures and demands robust infrastructure. The author argues that legacy, batch-oriented data systems are insufficient for modern AI, particularly for Retrieval-Augmented Generation (RAG), which requires real-time, low-latency data pipelines. To resolve this, the document proposes five key shifts for 2026, including the widespread adoption of real-time streaming infrastructure (like Change Data Capture), the elevation of data contracts into governance mandates, and the consolidation around lakehouse architectures. Furthermore, it addresses the paradox of AI automating foundational tasks, which necessitates data engineers pivoting to high-level architecture, governance, and AgentOps to manage fragmented AI agent ecosystems. Ultimately, the article asserts that AI success is now bottlenecked by data infrastructure maturity, requiring immediate investment in real-time platforms and automated governance.

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