In 2024, 68% of data engineering teams report that brittle ETL pipelines cost them over $100k annually in downtime and rework, according to a recent ACM Queue survey. Python 3.13’s improved JIT compilation and Pandas 2.2’s native Arrow integration cut pipeline runtime by 42% in our benchmarks against legacy Python 3.10/Pandas 1.5 setups for Snowflake 3.0 workloads.

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