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Data engineering in 2025 isn't about cool tools but about survival, as most current data engineers risk becoming replaceable commodities if they can't demonstrate real-world problem-solving skills and business understanding. Successful data engineers need to prove they've overcome significant challenges and understand the business impact of their work, not just technical implementation.

• Basic skills like Python, cloud certifications and ETL pipeline building are becoming commoditized
• AI and offshore contractors will replace engineers who only move data from point A to B
• Real data engineers can discuss their failures and what they learned from them
• Employers value candidates who can handle crises with business users breathing down their necks
• Understanding the cost implications of pipeline failures is crucial but rarely discussed
• The best engineers aim to automate themselves out of repetitive tasks
• Building something that breaks on purpose can help develop critical troubleshooting skills
• Documenting mistakes through detailed post-mortems demonstrates accountability and growth

Share your worst data blunder in the comments - what it cost you and your company. I'll highlight the most honest stories in a future episode, and might invite those with the most cringeworthy failures to join me for coffee on my podcast.

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Chris Gambill is a data engineering consultant and educator with 25+ years of experience helping organizations modernize their data stacks. As founder of Gambill Data, he specializes in data strategy, cloud migration, and building resilient analytics platforms for mid-market and enterprise clients. He’s passionate about making real-world data engineering accessible.

Connect with Chris on LinkedIn or learn more at gambilldata.com.