If you spend any time on tech LinkedIn or data Twitter, you've probably seen the name. No, I'm not talking about the quarterback who played for the Jets. I'm talking about Zach Wilson data engineer, the guy often referred to by his handle "EcZachly."
He's kind of everywhere. One minute he's posting a hot take about why you shouldn't "grind LeetCode," and the next he's breaking down how he jumped from a $30,000 salary to over $500,000 in roughly five years. It sounds like one of those "get rich quick" schemes you see in late-night infomercials, but the reality is actually rooted in some pretty hardcore engineering at places like Facebook, Netflix, and Airbnb.
The Viral Trajectory of a Staff Engineer
Most people know Zach for the numbers. He’s been radically transparent about his compensation, which honestly rubs some people the wrong way. But if you look past the dollar signs, the career path is wild.
He started out in 2014 making peanuts as a data analyst in Utah. By 2017, he was at Facebook (now Meta). Then came a stint at Netflix, and eventually, he landed a Staff Data Engineer role at Airbnb. For those who aren't in the tech bubble, "Staff" isn't just a job title. It's a senior-level tier that usually requires you to influence the entire company's technical direction, not just write a few SQL queries.
The jump from IC3 (Junior) to IC6 (Staff) by age 26 is what made him a bit of a legend—or a target for criticism, depending on who you ask.
Why he actually left Big Tech
In 2023, he did something that made a lot of people scratch their heads: he quit. He walked away from a $600,000 total compensation package at Airbnb. Why? To teach.
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He launched DataExpert.io, a platform focused on bootcamps and courses. It’s a gamble. Trading a guaranteed half-million-dollar paycheck for the life of a solo creator and educator is a move most people wouldn't have the guts to make.
What Zach Wilson Data Engineer Gets Right About the Industry
There’s a lot of fluff in the data world. You’ll see influencers talking about the "latest AI tool" every three seconds. Zach tends to ignore that. His philosophy is built on a few core pillars that actually matter in a real production environment.
Data Modeling is the real MVP
While everyone else is obsessed with whether they should use Snowflake or Databricks, Zach screams about data modeling. Honestly, he’s right. If your underlying data structure is garbage, it doesn't matter if you're using the fastest engine in the world; you're just producing "fast garbage."
He advocates for:
- Dimensional modeling (the Kimball stuff that everyone thinks is old but is actually still essential).
- Understanding Fact vs. Dimension tables at a deep level.
- Focusing on data quality before you ever touch a dashboard.
The "Sledgehammer" Problem
One of his most recent popular takes involved DuckDB vs. Spark. He often argues that engineers use a "sledgehammer" (like a massive Spark cluster) to crack a nut (a few gigabytes of data). He’s been pushing the idea that you can process a terabyte of data on a single machine if you're smart about it.
This is a refreshing change from the "scale at all costs" mentality that dominated the last decade of big data.
The Controversy: Why Some People Can’t Stand Him
You can't have 1 million followers across platforms without some haters. If you browse the r/dataengineering subreddit, you'll find plenty of threads complaining about his "recycled career advice" or his focus on FAANG (Facebook, Amazon, Apple, Netflix, Google) salaries.
Some critics feel that his advice is too tailored to the top 1% of tech companies. They argue that "average" data engineers working at a mid-sized insurance company in the Midwest can't simply "job hop to $500k."
There's also the ADHD factor. Zach is very open about being the "ADHD Engineer." While this resonates with thousands of neurodivergent people in tech, it also leads to a chaotic posting style that some find "noisy."
Is the DataExpert Bootcamp Worth It?
This is the big question. Since he’s pivoted to education, thousands of people have taken his free and paid bootcamps.
The Pros:
- It's practical. He teaches tools like Apache Flink, Apache Iceberg, and Spark based on how they are used at Netflix-scale.
- The networking. The community he’s built (especially on Discord) is massive.
- The focus on "Impact." He teaches you how to talk to stakeholders, not just how to code.
The Cons:
- It’s fast. If you're a total beginner who doesn't know what a JOIN is, you might feel like you're drinking from a firehose.
- Cost. The live cohorts aren't exactly cheap, though he does offer a lot of free content on YouTube.
The "EcZachly" Tech Stack
If you want to follow in the footsteps of Zach Wilson data engineer, you shouldn't just copy his resume. You should look at the tools he actually values. He’s not a "tool fanboy," but he has a clear preference for technologies that handle scale without breaking.
- SQL: Still the king. If you aren't a SQL master, you aren't a data engineer in his book.
- Python and Scala: He uses both, but often leans into the JVM side for heavy-duty streaming.
- Apache Flink: He’s a big proponent of real-time processing.
- Data Modeling: Again, this is his "hill to die on."
Actionable Steps for Aspiring Engineers
If you’re looking to replicate even a fraction of his success, don't just post on LinkedIn. Do the work.
- Master the Fundamentals: Stop chasing "AI/ML" if you can't build a robust ETL pipeline. Learn how to model data so it’s actually usable.
- Build in Public: This is how Zach got his start. He posted what he was learning and doing on LinkedIn every single day. It builds a "moat" around your career.
- Focus on Business Impact: Don't just say "I built a pipeline." Say "I built a pipeline that reduced latency by 40% and saved the company $200k in compute costs."
- Be Tool Agnostic: Learn the patterns, not just the syntax. If you understand how distributed compute works, you can switch from Spark to Flink without much trouble.
Zach Wilson is a polarizing figure, but he’s one of the few who has actually "seen the dragon" at the highest levels of data engineering. Whether you love his "hustle" energy or hate the FAANG-centric worldview, his technical contributions to the community—like the Data Engineering Handbook on GitHub—are hard to ignore.
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The industry is shifting. We're moving away from "big data" and toward "smart data." And honestly, that's exactly what he's been preaching for years.
Next Steps for You:
Check out Zach's GitHub repository for the "Data Engineering Handbook." It's a goldmine of free resources, roadmaps, and project ideas. If you’re serious about a career change, start there before dropping money on any bootcamp. Focus on the "Dimensional Modeling" section first—it's the foundation of everything else.