Data Engineer Academy

Need to calculate something that shouldn't show up in the final result? That's a job for a subquery, or a CTE if you want it more efficient and readable. Think of a CTE as multiple subqueries chained together into one clean SELECT.
The rule of thumb: one closed data set, start with a subquery. Multiple data sets that need to be built before combining, go with a CTE since it's the more efficient path.
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Thinking about changing careers? Your spouse may not care about the money as much as you think.

When you're considering moving into data for a higher-paying role, one common objection is:

“I need to talk to my wife/husband first.”

And sometimes, that's absolutely valid.

A career change can affect your family, finances, time, and future. Your partner may be less concerned about making more money and more concerned about your well-being and whether this decision is right for your family.

So instead of simply trying to convince them, have a real conversation about:

Why you want to make the change.

What isn't working in your current career.

What the potential benefits are.

How the transition could affect your family.

Why you believe this could be better for everyone.

The goal isn't to “win” the conversation. It's to help your partner understand why this matters to you—and how it could benefit your family.

Short:
Comment DATA97 and we’ll send you access.

👇 Watch the free training below.

https://smpl.is/amsrw

You shouldn't have to figure out your data career alone.

Inside the DEA community, members can:

Get resume reviews and job referrals.

Connect directly with leadership and experienced data engineers.

Join weekly group calls with instructors.

Learn from professionals with 10–30+ years of industry experience.

Network with other people building careers in data.

Learn how to enter the data space and increase their earning potential.

The goal isn't just to give you information.

It's to give you access to people, guidance, and a community that can help you move forward.

Value Driven:
Want the full Data Engineer Academy community for just $97/month? Comment DATA97 and we’ll send you the link.

👇 Watch the free training below.

https://smpl.is/amsrn

Your happiness at work might be keeping you stuck.

A mentor once asked Chris, “How happy are you?”

His answer? 7/10.

The mentor told him, “That’s the most dangerous number you could be.”

Why?

Because 7 feels decent enough to stay—but not good enough to be truly fulfilled.

When you're at a 5 or 6, the problems may push you to make a change.

But at 7, you're comfortable.

And that comfort can make it harder to explain to your spouse why you want to take a career risk.

The first step is getting honest about where you really are on the happiness scale.

You need to understand your own reasons before you can confidently communicate them to someone else.

Direct:
Want access? Comment DE97 and we’ll DM you the details.

👇 Watch the free training below.

https://smpl.is/amsqf

You don't have to quit your job to make a major career jump.

One of the biggest mistakes early-career professionals make is thinking they need to quit or get another degree before they can transition into data engineering.

You can start on the side.

Even 1–2 hours a day can compound when you stay consistent.

A practical approach:

Spend 30 minutes a day building your SQL skills.

Learn in-demand tools like DBT, Airflow, Kinesis, and Kafka.

Apply broadly to data engineering roles.

Tailor your resume to the positions you're targeting.

Build an efficient application strategy instead of applying randomly.

You don't need to change everything overnight. You need a consistent system that moves you forward.

Curiosity:
If you want to see what’s inside, comment DE97 below and we’ll send everything over.

👇 Watch the free training below.

https://smpl.is/amsrv

The data industry is changing—and Chris Garzon built DEA to help tech professionals keep up.

As the Founder and CEO of Data Engineer Academy, Chris has spent years working in the data industry, including experience at Amazon, Lyft, and startups.

For the past 3 years, DEA has helped 1,000+ professionals transition into higher-paying data roles.

But the mission goes beyond getting a new job.

It's about helping tech professionals build the skills they need to stay valuable in an AI-driven future.

The data landscape is evolving quickly.

The professionals who continue to learn, adapt, and upskill will be better positioned for what's next.

Direct:
Want access? Comment DE97 and we’ll DM you the details.

👇 Watch the free training below.

https://smpl.is/amsrm

Being 7/10 happy at work might be more dangerous than you think.

You're not miserable. But you're not excited either.

You might be underpaid, undervalued, stuck in a dead-end role, or no longer learning anything new.

The problem is, when things are “good enough,” you may not feel enough urgency to make a change.

Even your spouse may not understand why you want to leave—not because they don't support you, but because they may not have the expertise to evaluate your career opportunities.

Before convincing anyone else, get clear on why you need the change.

Sometimes, “good enough” becomes the thing keeping your career stuck.

Individual results vary.

Simple:
Comment DATA97 below and we’ll send the link right over to you.

👇 Watch the free training below.

https://smpl.is/amsqa

One behavioral question appears more often than any other in data interviews.

After analyzing approximately 1,000 data analyst and data engineering interview rounds, the DEA team found this question came up most frequently:

“How do you prioritize when you have multiple tasks to complete?”

A strong answer should go beyond saying, “I do the most important task first.”

Use a prioritization matrix to evaluate each task based on:

Urgency.

Importance.

Business impact.

Deadlines and dependencies.

If something is both urgent and important, it should typically take priority.

But interviewers also want to know how you communicate tradeoffs, align expectations with stakeholders, and respond when priorities suddenly change.

They’re not simply asking how you manage a to-do list.

They’re evaluating how you make decisions when everything feels important.

Value Driven:
Want the full Data Engineer Academy community for just $97/month? Comment DATA97 and we’ll send you the link.

👇 Watch the free training below.

https://smpl.is/amm12