1 link tagged with all of: scaling + data-engineering + data-architecture + burnout
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AI is creating more work for data teams without corresponding budget increases, forcing engineers to maintain infrastructure instead of building. The article walks through architecture decisions and tool choices that let small teams scale operations without collapsing under demand.
- Only 30% of companies increased data budgets in 2025, yet expectations for governance, observability, and self-service features keep rising—most teams must deliver more with the same headcount
- Data volumes and citizen automations (via tools like n8n) multiply dependencies faster than teams can manage them; without proper orchestration and visibility, this creates invisible work that scales directly with data growth
- Pick infrastructure built for scale (Snowflake, Databricks) paired with a single control plane (like Orchestra) rather than a modular stack that requires constant manual intervention and cluster management