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We'll help you land your dream data role 🚀
Helped over 300 + counting
Data Engineering | Data Analysis | Cloud Engineering
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https://dataengineerinterviews.com/fb-organic?el=profile&htrafficsource=fborganic

10/11/2026

Getting ghosted after applying for a job? Don't assume it's always a rejection.

According to the video, many applications simply receive no response at all.

And that's where recruiter follow-ups can make a difference.

Instead of sending one application and waiting indefinitely, consider following up professionally and giving the recruiter another opportunity to see your message.

Why might someone not respond?

→ They may not have seen your original email
→ Your message could have been filtered into spam
→ They may be out of the office
→ Your application may have been buried under dozens of others
→ They may need another reminder that you're genuinely interested

The video also shares that following up a second time can significantly increase the chance of getting a response.

The goal isn't to spam recruiters.

It's to follow up strategically, professionally, and at reasonable intervals.

Because sometimes, getting a clear “no” is better than sitting in silence wondering what happened.

And if you're unsure what to say, DEA is offering a free GPT designed to help create recruiter follow-up emails.

If you've got 3+ years in tech and you're wondering what your next move should be, this free video is a good place to start → https://smpl.is/an9xy

10/11/2026

Does a data engineering portfolio really matter more than your resume?

According to Chris, not necessarily.

It depends on what you mean by “portfolio.”

If your data engineering projects are clearly included on your resume, they can help demonstrate that you have relevant experience with the technologies and skills listed in the job description.

But there's a difference between:

Showing relevant projects on your resume

and

Spending months building an extensive GitHub portfolio that recruiters may never open.

Recruiters aren't always technical enough to evaluate every line of code in a GitHub repository.

Their role may be to identify whether your background matches the requirements of the position and then move qualified candidates forward to someone more technical.

So instead of asking:

“How impressive can I make my GitHub?”

Ask:

“Does my resume quickly show that I can do what this job requires?”

For data engineering, focus on projects that demonstrate relevant skills and technologies—and make sure those projects are easy for a recruiter to understand from your resume.

Your portfolio should support your job search.

It shouldn't become a project that takes months without a clear purpose.

🚀 Want more practical strategies for breaking into data engineering?

AI isn't going anywhere. But every AI model runs on data, and somebody has to build and maintain the pipelines behind it. The engineers who get that are going to be in demand for a long time. If you want to be one of them, watch this free video on how we help tech pros make the move → https://smpl.is/an9xc

10/11/2026

🚀 READY TO LEVEL UP YOUR DATA CAREER?
Your current skills might be enough to get started—but the right community can help you turn those skills into real opportunities.

Inside the Data Engineer Academy Skool Community, you can connect with people who are also building their careers, learn from practical industry insights, get guidance, and stay surrounded by others who are serious about growth.

You don’t have to figure everything out alone.

Learn. Build. Connect. Grow.

Want the full picture? I made a free video on how we help experienced tech pros move into higher paying data roles, without starting over. Watch it here → https://smpl.is/anb04

10/11/2026

The apply-for-you strategy, from a DEA student's point of view: you can send out hundreds if not thousands of applications on LinkedIn and other job boards and maybe only get a handful of calls back. Knowing who to present your profile to, and when, is extremely helpful in their experience, and it is partly why they joined.

If you're ready to stop guessing and start with a real plan, go watch this free video. It shows you exactly how we get tech pros in front of hiring managers → https://dataengineerinterviews.com/fb-organic?el=10-07-2026-apply-strategy-students-point&htrafficsource=fborganic

10/11/2026

Trying to break into the data field for the first time? Your first role doesn't have to be called “Data Analyst.”

One thing that can make a career transition easier is understanding just how many roles involve working with data.

An analyst can work across different industries and functions, including:

→ Data Analyst
→ Business Analyst
→ Marketing Analyst
→ Financial Analyst
→ Healthcare Analyst

The title may be different, but the underlying work can still involve analyzing information, identifying patterns, creating reports, and helping businesses make decisions with data.

So if you're trying to enter the data field, don't limit your search to one job title.

Instead, ask:

“What roles can help me gain relevant data experience?”

Your first role can become a stepping stone toward more specialized opportunities later.

The key is to understand your existing skills, identify the roles where they transfer, and build from there.

Don't let a job title limit your view of the data career path.

🚀 Want to learn more about transitioning into data?

You don't need another certificate. What you need is a clear path, real projects, and someone who's already done it showing you the way. That's what this free video is about → https://smpl.is/an9yy

10/11/2026

On the fence? One DEA student has a message: get off the fence and jump in. They say the program moves at your pace and wants to get you into a better position, and the access is real: questions asked on Slack get responses within minutes from coaches and mentors, with tips and hints on how to improve what you are working on.

You don't need another certificate. What you need is a clear path, real projects, and someone who's already done it showing you the way. That's what this free video is about → https://dataengineerinterviews.com/fb-organic?el=10-07-2026-fence-message-get-fence&htrafficsource=fborganic

10/11/2026

Worried tech is too daunting if you come from a non-technical background? A DEA graduate says it is not as daunting as they thought. With the base knowledge you get from SQL and a couple of projects, most companies, including the one they started with, onboard you into the role and want to teach you the job. As long as you have that base knowledge, they say, stepping in becomes very easy.

If you've got 3+ years in tech and you're wondering what your next move should be, this free video is a good place to start → https://dataengineerinterviews.com/fb-organic?el=10-07-2026-worried-tech-daunting-come&htrafficsource=fborganic

10/10/2026

An LLM chain, explained with a car. The prompt is the fuel, the LLM is the engine, and the output is the distance the car covers. An LLM chain links a prompt template and an LLM so they work as a single unit. A chain is just a sequence of operations: build the prompt, send it to the LLM, parse the output. The LLM chain is the common chain that does the first two.

AI isn't going anywhere. But every AI model runs on data, and somebody has to build and maintain the pipelines behind it. The engineers who get that are going to be in demand for a long time. If you want to be one of them, watch this free video on how we help tech pros make the move → https://dataengineerinterviews.com/fb-organic?el=10-07-2026-llm-chain-explained-car&htrafficsource=fborganic

10/10/2026

Learning was never the limiter. Coursera, Code Academy, AI tools, Reddit and Stack Overflow are all free. The belief DEA's founder wants to break is 'I'm learning but nothing has changed with my compensation.' His take: learning to code SQL is different from interviewing in SQL, and the application process is probably where you are doing it wrong.

I started as a data analyst at Amazon making around 60 grand. Several years later, I was at Lyft making close to 500. It wasn't because I was the smartest person in the room. It was the sequence. If you want to see the same playbook we use with our students, watch the free video here → https://dataengineerinterviews.com/fb-organic?el=10-07-2026-learning-never-limiter-coursera&htrafficsource=fborganic

10/10/2026

When is the right time to leave your job?

It's a question many professionals think about—but often only when something goes wrong.

According to Chris, one of the biggest mistakes is treating your current job as if it will always be there.

The reality is that no job is 100% guaranteed.

That doesn't mean you should quit impulsively.

It means you should be thinking proactively about your career—even when things are going well.

Ask yourself:

→ Are my skills still relevant?
→ Am I continuing to grow?
→ Is my compensation aligned with my market value?
→ What opportunities exist outside my current company?
→ If my role disappeared tomorrow, would I be prepared?

Career security isn't necessarily about staying in one job forever.

It's about making sure you have options.

You don't have to be actively planning your resignation every day.

But you should know where you stand, continue developing your skills, maintain your professional network, and stay aware of what's happening in the market.

Don't wait until you need a new job to start preparing for one.

🚀 Want to build a stronger data career and keep more options open?

You don't need to start over. You need to level up. Here's the free video that shows you how → https://smpl.is/an9xu

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https://dataengineeracademy.com/

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