There’s something magical about building on Snowflake. It feels like you’re on the cusp of data nirvana: effortless scalability, near-infinite concurrency, and the promise of turning raw data into actionable insights without the headache of infrastructure management. But as any seasoned data practitioner will tell you, the magic can fade faster than you think if... Continue Reading →
Error Handling in Data Pipelines: Building for the Inevitable
Data pipelines are like highways designed to keep traffic flowing smoothly. But what happens when there’s a crash? In data engineering, errors aren’t an exception they’re inevitable. The real question is: do you have the guardrails to handle them? Why Error Handling is Different in Data Engineering Unlike application code, pipelines don’t just “throw and... Continue Reading →
Logging Like Data Engineers: Turning Debug Logs into Gold
Logging often feels like cleaning your room you don’t want to do it, but when things go wrong, you’re glad you did. For Data Engineers, logging isn’t just about writing messages it’s about creating a narrative that helps you trace, debug, and optimize pipelines that span terabytes of data. Done right, debug logs become gold:... Continue Reading →
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