The SHOCKING Truth About Becoming a Data Engineer in 2026

⬇️ Click here to learn how to land a high paying data engineering role NOW ⬇️ https://dataengineerinterviews.com/op...

Data engineering has officially become the highest-paying data role this year—and it's not slowing down. Companies are scrambling to hire skilled data engineers who can build the infrastructure that powers AI, analytics, and business decisions at scale.

If you've been thinking about pivoting your career or leveling up in tech, now is the time. The demand is real, the salaries are competitive, and the opportunities are everywhere.

Ready to make the switch? A quality data engineering course can take you from beginner to job-ready in months, teaching you the exact skills companies are hiring for: SQL, Python, cloud platforms, data pipelines, and more.

Don't wait for the "perfect moment"—2026 is your year to invest in yourself and land a role that pays what you're worth.

(00:00:00) Introduction - 25 Things Learned in 2025
(00:02:15) Lesson #1 - Fear Costs Millions of Dollars
(00:08:30) Lesson #2 - Skepticism is Overrated, Research is Underrated
(00:11:45) Lesson #3 - Free is Expensive
(00:14:20) Lesson #4 - Blaming the Market is Easy, Yourself Not So Much
(00:17:10) Q&A - How to Practice Python for Data Engineering
(00:18:00) Q&A - Overcoming the Degree Gap
(00:19:15) Lesson #5 - More of the Right Thing Works
(00:23:40) Lesson #6 - Soft Skills are the #1 Reason Engineers Fail Interviews
(00:26:30) Q&A - Getting into Data Engineering with Backend Experience
(00:27:45) Lesson #7 - Can You Be a DE Without Coding?
(00:29:20) Lesson #8 - Age is Not the Problem
(00:31:50) Lesson #9 - Don't Quit Your Job to Learn
(00:34:40) Lesson #10 - Tool Overwhelm is Destroying Your Chances
(00:37:25) Lesson #11 - Which Companies Pay $150K+
(00:42:10) Lesson #12 - Most Important Tools to Learn
(00:45:30) Lesson #13 - Do You Need to Take a Pay Cut When Transitioning?
(00:49:15) Lesson #14 - How Long Does It Really Take?
(00:52:40) Lesson #15 - Leadership is Misunderstood
(00:57:20) Lesson #16 - Legacy Stacks Hurt Your Career
(01:00:35) Lesson #17 - Am I Competitive?
(01:03:50) Lesson #18 - Do You Need a GitHub Portfolio?
(01:06:15) Lesson #19 - Is TPM a Good Route?
(01:10:00) Lesson #20 - Zero Interviews in 100 Applications
(01:13:45) Lesson #21 - Data Analyst vs Data Engineer
(01:16:20) Lesson #22 - Do You Need Real World Projects?
(01:19:05) Lesson #23 - Pay or Title - What Matters More?
(01:22:30) Lesson #24 - Interviewing is the Game
(01:24:50) Lesson #25 - AI Won't Replace Data Engineers
(01:28:15) Closing Remarks

If you’re new to my channel, my name is Christopher Garzon. I run the top Data Engineering Academy in the country, where we help students transition into data engineering from other data professions to increase their compensation.
How I got here…
At 18 years old, I started at Boston College.
At 20, I was sneaking into graduate-level classes to take machine learning and data science courses.
At 21, I invested in a data science course from a mentor and wired him $3,000 without ever meeting him.
At 22, I landed my first job as a data analyst at Amazon, making $60,000 per year.
At 24, I became a data engineer at Amazon, increasing my salary to $100,000 and started angel investing in a couple of data companies.
At 25, I moved to a startup as a data engineer and doubled my income to $200,000 per year.
At 26, I was making about $350,000 at Lyft.
At 27, Lyft stocks went up, and my total compensation reached around $450,000. That same year, I launched the Data Engineering Academy.
For the last two and a half years, I’ve been running the Data Engineering Academy full-time, helping thousands of people transition into data engineering and significantly increase their earning potential.
To all the data professionals grinding—your journey is still being written. The bigger the obstacles, the greater the story.
Remember, don’t settle for your next job. Go for a better one.
Chris

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⬇️ Click here to learn how to land a high paying data engineering role NOW ⬇️ https://dataengineerinterviews.com/op...