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⬇️ Click here to learn how to land a high paying data engineering role NOW ⬇️ https://dataengineerinterviews.com/optin-yt-org?el=dec25AMA&htrafficsource=ytorganic
Looking for the right data engineering course and have questions about career transitions, salary expectations, and job placement? In this live Q&A session, Chris Garzone (CEO of Data Engineer Academy) answers real questions from aspiring data engineers, TPMs, data analysts, and career switchers about breaking into high-paying data roles in 2025.
If you're researching data engineering courses, wondering about job placement rates, or trying to understand if you can transition from your current role (software engineer, data analyst, healthcare, project manager) into data engineering, this session covers everything you need to know before enrolling in any data engineering course or bootcamp.
More Resources:
- Learn Snowflake in 2 Hours: https://youtu.be/mP3QbYURT9k?si=722dm-5hvWFeOqnB
- How to Ace the Data Modeling Interview: https://youtu.be/YFVhC3SK0A0?si=YGLS3wjYHhdwYpVA
- Don't Get Replaced by AI: https://youtu.be/hMZrHIJshFU?si=aX7NeTxohBLHNZ3j
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
00:00:00 — From $60K at Amazon to ~$500K as a Data Engineer (My story)
00:00:19 — What this AMA is about and who it’s for
00:00:33 — Why most people are doing tech job searching wrong
00:00:52 — What you’ll gain from watching this AMA
00:01:01 — AMA begins
00:01:10 — Project Manager → TPM: how Data Engineer Academy helps
00:02:20 — What a TPM actually does (role breakdown)
00:02:55 — Job placement timelines: how long it really takes
00:04:02 — Placement rates explained (who succeeds and why)
00:05:20 — Desktop Support → Data Analyst: personalized curriculum
00:05:54 — Filling skill gaps (SQL vs Python & data visualization)
00:06:17 — Scaling job applications and why it takes hundreds
00:07:03 — Projects explained: choosing vs highest-impact recommendations
00:07:49 — Slack access issues addressed
00:08:59 — Mentor-to-student ratio
00:09:46 — How people reach $400K–$600K (US vs Canada, visas, comp)
00:12:32 — Program cost breakdown ($10K–$50K)
00:13:17 — Backend Dev → Data Engineer + AI impact on data roles
00:14:18 — Booking a call & how the team helps candidates
00:14:44 — Will AI replace data analysts?
00:15:25 — The 20-interview guarantee explained
00:17:01 — Data Engineering → AI: how big is the gap?
00:18:06 — AI-only pathway explained
00:18:43 — No data background (healthcare): should you go for it?
00:19:16 — Mindset, consistency, and why most people fail
00:19:36 — NYC job market: remote vs hybrid vs in-office
00:21:34 — DevOps / IT PM → Data & AI roles
00:22:39 — Why TPM in Data is the strongest cross-functional fit
00:23:35 — Why AI + analytics is a growing niche
00:26:34 — How to test if data engineering is right for you
00:28:03 — The real “bet on yourself” decision
28:57 — UK/London question begins (international support)
⬇️ Click here to learn how to land a high paying data engineering role NOW ⬇️ https://dataengineerinterviews.com/optin-yt-org?el=dec25AMA&htrafficsource=ytorganic
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