Let’s say you meet someone and reach the point of the conversation where you ask them what they do for a living. They tell you they are a data engineer. Not wanting to look silly, you act as if you understood what that meant.
If that led you here, don’t be ashamed: it’s not a well-understood career (yet). And don’t worry — in this article, we will take you through exactly what data engineering is, how it can be distinguished from other IT professions, and why they’re so significant to business.
What do data engineers do?
If you’ve looked up what data engineers do, there’s a good chance you’ve found many complex definitions that didn’t quite make sense. Don’t fret. I’ll keep it simple while also retaining the core of what a data engineer is:
Data engineers take raw data and make it easy to work with.
So it’s often about:
- Dealing with and reducing duplicate data.
- Simplifying difficult-to-access data.
- Filling in missing values.
- Making the data integrative in different domains.
And that last point is vital: data engineers are the “tech guys” for the non-tech guys. They make the data available for everyone, not just information technology professionals.
Data engineers are also responsible for something known as “the Single Source of Truth (SSOT). “What on earth is this?” You might be wondering.
Well, the SSOT is aggregated data from various systems into one single location.
This single location will be helpful for the analytics and data science teams.
Services data engineers offer
Data engineering is a very versatile role, so the services data engineers offer will vary quite a bit. Companies that specialize in data engineering will typically offer end-to-end data solutions. These will be custom data solutions for collecting, organizing, and visualizing the data.
If we were to expand on this, we can say data engineers offer:
- Data ingestion, storage, and integration: This process compiles and moves data to a cloud storage platform as a central database. It also involves creating data connection channels.
- Data processing: This is taking data and turning it into information. Here, duplicates and errors are removed as well.
- Business intelligence tools: These tools take the information and provide graphical and meaningful representations.
How do you become a data engineer?
First, let me start by saying that data engineering is a great career choice. Numerous studies show that the need for data engineers is progressively increasing.
So, how do you become one? Because data engineering is only an emerging job, it’s not really possible to study directly at universities or colleges. That said, some qualifications put you in good stead for a career in data engineering; these are as follows:
- Software Engineering
- Data Science
Typically, people will get their first entry-level jobs with one of these qualifications and then, through experience, grow into new positions within data engineering.
This is a long path but also a lucrative one. The average data engineer earns $123,576 per year.
Why are data engineers important to businesses?
It goes without saying, but modern businesses need data engineers. Once they’ve set up data architecture, data engineers assist analytics teams with reaching conclusions and creating reports vital for business success.
In addition, data engineers help integrate AI solutions, which can improve data flow between systems.
These professionals also have a vital optimization role, helping businesses determine the best use of resources, ultimately maximizing performance.
Finally, by ensuring solid data governance, data is protected. Therefore, potential data breaches are mitigated.
This all sounds very abstract, so here’s a concrete example to help it all make sense.
A practical example of data engineering
Think about a clothing store; let’s call it Cool Kidz Clothes. They’re looking to improve their online customer experience by creating a way for them to get personalized recommendations.
Of course, this means a lot of data collection. This is where a data engineer comes in.
Data engineers will, in this case:
1. Set up the data architecture needed.
2. Clean and process the data.
3. Store the data in the operating locations.
4. Integrate AI and fine-tune processes for the purpose of streamlining.
5. Offer continual support to the analytics team, who will use the data.
After these five steps, Cool Kidz Clothes is now on its way to improving its website, ultimately increasing sales and improving customer retention.
That’s the power of data engineering.
A new age
We’re in a new age known as the information age. And with this comes a lot of changes. One of these changes is the integration of data management. After all, what’s the use of having all this data if it isn’t used efficiently and effectively?
Data engineers play a vital role in making the best use of this data and supporting non-technical teams.