Is Data Engineering for You? 5 Traits You Need to Know
Curious if data engineering is your ideal career? Discover the five key job traits, and see if you have what it takes to thrive in this technical field.
Greetings, curious reader,
Is data engineering the right job for you? It can be tough to decide. Data engineering can seem confusing, and many people don't know what it involves.
By the end of this article, you'll know more about the role. You'll have a better idea of the skills it takes, what challenges to expect, and the type of work you'll do.
In this article, I will explain five key traits of the data engineering role. You'll see how data engineers fit into a company, what makes the job both hard and rewarding, and why it can be a great choice.
If you like solving problems, writing code, and working behind the scenes, data engineering might be the perfect career path for you. Let's get started!
Reading time: 8 minutes
Trait #1: It's Hard to Explain What You Do
As a data engineer, you may find that most people won't understand what you do. Even other developers might be confused when you talk about your work. They hear the word "data" and think you are doing your job is either too complex or too boring.
You might need to explain your job in different ways depending on who you're talking to. For example, if you're talking to developers, you can focus on the coding and infrastructure part.
But if you're speaking with business leaders, you might need to explain how your work helps them make better decisions. It can be frustrating when people don't get it, but it also shows how specialised your role is.
We've discussed how to explain your job before. Read this article if you want to learn how to do it in an approachable way.
Despite the confusion, the job is far from dull. You'll always be solving new problems and learning new things.
Data engineering can be very rewarding if you like being the go-to expert in bridging business and tech. It just takes some creativity when explaining your role to others.
Trait #2: There's a lot of Coding Involved
If you like writing code, then you'll enjoy data engineering. This job involves coding all the time.
Think of yourself as an architect for data. You'll design and build systems that move data from one place to another. These systems must be reliable and scale as the business grows.
You'll also deal with how much the systems cost to run. And you'll need to make them as efficient as possible.
You can learn more about the importance of systems design in data engineering in this newsletter.
The good news is you'll use different programming languages and tools. SQL and Python are the standard in data engineering, but you might also use tools like Apache Spark or cloud platforms like AWS.
But there's so much more. For example, I am currently working on an extremely high throughput data platform using TypeScript and Timescale DB.
If you have a background in software development (been there, done that), the coding part of data engineering will feel familiar. And if you like problem-solving, you'll love tackling the challenges that come with scaling and improving data systems.
Trait #3: You Directly Impact the Business
One of the best parts of data engineering is your direct impact on the business. Many tech jobs feel disconnected from the company's core goals.
But in data engineering, your work directly affects how decisions get made. You'll work with internal teams like analysts or business stakeholders who need data to make smart decisions.
This gives you the chance to learn a lot about how the business works. You'll start to understand which metrics are important and how they influence business strategy.
You'll see how different events—like sales or customer behaviour—drive decisions. In many ways, you'll learn as much about the business as someone studying for an MBA.
I’ve written many articles about the relationships between data engineers and business stakeholders. This one is very relevant here:
The more you interact with the business side, the more valuable you become. You're not just building data pipelines—you're making it possible for the company to use data in the best way.
As you continue working in data engineering, you'll gain insight into how the entire business functions. This work is what makes your role feel more connected to the bigger picture.
Trait #4: Data Engineers Are Often Undervalued
Many companies don't fully understand how vital data engineers are. They often hire data analysts and scientists but forget to invest in their data engineering teams.
This can leave you in a small group of engineers handling the entire data infrastructure for a large organisation. It's common to see a company with hundreds of employees but only one or two data engineers. Don't ask me. I don't want to talk about this.
This puts extra pressure on you. As the company grows, the data systems become more complex. But if the company doesn't expand the data engineering team, it creates a bottleneck.
It can feel like the work is never-ending, and you may have to work hard to keep up with demand. Even though data engineers are critical to making sure the business can use its data, many companies don't see this right away.
The good news is that this is changing. As businesses start to see the limits of small data engineering teams, they realise they need to invest more. But until then, you may have to prove the value of your work.
By explaining how better data infrastructure helps everyone else do their jobs, you can help push for more support and resources. Over time, your role will get the recognition it deserves.
But please, do not overwork yourself. No job deserves risking your health!
Trait #5: You Solve Complex Problems Behind the Scenes
If you expect applause for your job, data engineering is not for you.
In data engineering, most of your work happens behind the scenes. You'll build and maintain systems that move large amounts of data smoothly. The goal is to make sure data is clean, organised, and ready for others to use.
When everything works well, no one notices. It's only when something breaks that people ask what's going on.
Think about it for a minute: If you work in one, you just expect the road to your office to be open. It's just there. You don't care who built it and how. You just need it so you don't get fired.
It's the same with data engineering. People will only think about you when they need somebody to shout at because they can't do their job.
Your job involves solving tricky technical problems that aren't always visible to others. You'll need to figure out how to make sure your systems can handle more data as the company grows.
You'll also need to think about how to keep costs low while making sure the data pipeline runs efficiently. This is where your skills as a coder and problem-solver really come into play.
Your role is to make sure everything runs smoothly in the background. It's not glamorous, but it's important. If you like figuring out how to make systems better and faster, this part of the job will be a great fit for you.
Data engineering is a thankless job, but it's cool. Not getting as much external appreciation is fine as long as you are happy with what you do.
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Final Thoughts
Data engineering is a job that many people don't fully understand. Some think it's just a support role for data scientists or analysts. Others may confuse it with data science itself.
But this misunderstanding actually gives you a huge opportunity. Because many people don't get what you do, you can carve out your own space in the organisation. You can show how important your role is and how it impacts everything else.
Think about it—when others don't fully see the value you bring, you have the chance to educate them. You can explain how clean, reliable data is the foundation for all business decisions. You can position yourself as a critical piece of the company's data strategy.
As technology advances, tools like AI and cloud services are making some parts of data engineering easier. Automating repetitive tasks, managing infrastructure, and scaling systems are now less challenging than before.
These tools handle many of the heavy-lifting parts of coding. But this shift gives you more room to focus on value-adding activities.
Instead of spending all your time managing pipelines, you can focus on building smarter, more efficient systems. You can help solve bigger business problems by making the data infrastructure even more robust and aligned with business goals.
In other words, these tech advancements don't take away from your role. They give you more time to work on the parts of data engineering that make the biggest impact.
Summary
Data engineering is a challenging and rewarding career. You'll spend a lot of time solving complex problems, coding, and working behind the scenes.
Your work will have a direct impact on how the business operates, but it may not always get the attention it deserves. The role often feels undervalued, but that's changing as companies realise how much they depend on good data infrastructure. If you enjoy coding and problem-solving, data engineering offers endless learning opportunities.
So, is data engineering a good career for you? If you like being behind the scenes, tackling big technical challenges, and learning how data drives business, the answer is yes.
The opportunities in data engineering are huge—you just need to be ready to seize them. Focus on building your skills, understanding your company's data needs, and staying up to date on new tech. With the right mindset and skills, you can turn data engineering into a long and successful career.
Did you like this article? Stick with me because next week, you and I will discuss how you can leverage AI to speed up your coding. It really works!
Until next time,
Yordan
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Nice post. I agree with all these, except #3. I see Data Engineers too frequently removed from the business to see and understand how their data is used. However perhaps that's just my narrow view. In an ideal world they would get to see it as you describe.