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What Is the Future of the Data Engineer?

If you are wondering about the future of data engineering as a career and whether it is worth becoming a data engineer, then this article is for you. Here, I cover how lucrative the prospects are for data engineering and how you can get started and thrive in the domain.

“Data” is probably one of the most used terms in our everyday business language today. A data engineer plays a pivotal role in developing the infrastructure required for data-related actions. So, it is no surprise data engineering is one of the most sought-after jobs by professionals today.

If you are an analyst, you probably use some form of data to come up with insights to grow your business or to solve a business problem. If you are managing a department like marketing, finance, operations, or HR, you are using the conclusions from these analyses daily to make business decisions. And if you are a student waiting to enter the corporate world, you probably want to learn about how data affects customers and businesses and use these skills for your career.

At the same time, you as a customer are creating and consuming data, consciously or unconsciously. Take Google for instance. Can you fathom more than 5 billion user queries a day on the search engine? Google works with petabytes of information (one petabyte = 1,000,000 GB). Uber, Facebook, Netflix, and several other organizations including those run by the government, work with varying volumes of data, making all of us key consumers of such systems.

The adoption and usage of these applications by customers are key to business success. And the design of the data and information flow is one of the most critical contributors to this usage. Would you use Airbnb if it takes an hour to retrieve a list of properties? Query a search engine if the results are irrelevant? Or book a flight through a website if each flight search takes 20 minutes to retrieve? Probably not, especially when you are inundated with several platforms that can do the job faster and better.

All these use cases have become thoroughly intertwined in every part of our lives today. This is not a temporary fad but rather a megatrend here to stay. And since data engineering lies at the very core of this megatrend, data engineers have a bright future.

What Is the Future of the Data Engineer?

What makes the data engineering job both challenging and interesting is the sheer volume of data we work with these days and the impact a smart use of this data creates. And in my opinion, the industry even today is supply-constrained for capable data engineers.

So, if you are contemplating making a career as a data engineer or are already in the field mulling over your growth trajectory, don’t bother! You have a long and successful career ahead of you.

In this article, along with what the future may hold for data engineering, I will cover important skills required to be a data engineer and the types of jobs and salaries to expect if you master these skills. But first, let me take you through the key responsibilities of a typical data engineer and the kinds of projects you may work on.

Key Responsibilities of a Data Engineer

Imagine your friend has started a new e-commerce marketplace that sells footwear and clothing online. You are the data engineer for the project.

An e-commerce marketplace typically has several sellers who list their products on the portal. Customers then browse through the catalog and buy items. On any given day, various sellers and buyers interact with the e-commerce website.

Buyers search for products, add them to their carts, buy items, see their past orders, and so on. Sellers upload product listings, enter relevant information, look at their sales data and other analytics to help them sell more.

A data engineer ensures the right data structures and systems are in place to store and get relevant information. Since thousands of customers may access the interface concurrently, the algorithms and the underlying retrieval mechanisms should be efficient, reducing transaction times and ensuring accuracy.

In addition to making sure the customer experience is adequate, the data related to orders, items in the cart, and customer browsing patterns are also important for the management and for the platform itself to further boost sales and/or reduce cost. A data engineer ensures such data is available in a usable format for data scientists or analysts to consume.

This is a critical difference between the two. A data scientist helps answer questions like “what is the typical spending pattern for a particular customer segment?” or “what are the popular items in a particular geography?”

In contrast, a data engineer ensures the collected data is sufficient and available for analysis by the data scientist. In short, a data engineer is responsible for creating data pipelines, collection mechanisms, data structures for storage and retrieval, and algorithms for faster and concurrent processing of this data.

Sounds complicated? Don’t worry! The more you acquire the right set of skills and the right understanding, the easier it becomes.

What Is the Future of the Data Engineer?

So, how can you become a good data engineer? What are the key essential skills for success?

How to Become a Data Engineer: Basic Skills

As a data engineer, one of the most important systems on which you design your structures is the database itself. And you need SQL to talk to the database! You need to master SQL if you want to make the impact the domain demands.

But where do you start? You don’t need a fancy computer science degree to take the first steps. Many online learning resources give you the right impetus.

If you are new to SQL, I recommend the SQL Basics course from The beauty of this course is twofold: first, the design of the course itself that is simple to learn yet effective, and second, the examples and the practice queries you write as part of the course.

This course is useful for anyone interested in working in fields that require data manipulation. Specifically for a data engineer, understanding how and which data structures to create is equally important. For that, the SQL track focused on the creation of data structures is especially useful.

Learning SQL gives you a solid foundation, but it is not sufficient. I recommend learning about Big Data and Hadoop as well. If you are more of a book nerd, here is a list of the best books to read to learn about data engineering.

Other hard skills that help include:

  • Python.
  • Some concepts of NoSQL (especially for unstructured data such as documents).
  • Kafka.
  • AWS.

Apart from these skills, focus on certain ways of thinking and best practices. In my opinion and experience, the following points make a big difference in your career growth.

  • Always keep the customer at the core and work backward from their needs.
  • Keep things simple and do not overcomplicate your algorithm or data structure design.
  • Focus on speed, but more importantly, on accuracy and quality.
  • Stay in touch with the business regularly at every stage of development.
  • And most importantly, never lose track of the big picture and the project objectives.

If you work hard enough to acquire the needed skills, follow these basic principles to avoid common mistakes to succeed as a data engineer.

Growth of Data Engineering Jobs

So far, we have established why data engineering jobs will continue to be relevant in the future. We’ve also established how to become a data engineer. Now, let us take a deeper look at the growth prospects.

In terms of the number of jobs posted compared to other data-related jobs, data engineering ranks number one with almost a 50% growth rate. Check it out here. In recent years, the demand for data engineers has surpassed the supply.

What Is the Future of the Data Engineer?

Source: Towards Data Science

Well, no wonder! The average salary for a data engineer in the U.S. is as high as $116K. Top companies pay even higher.

This makes data engineering one of the highest-paid data-related jobs today. So, is it worth becoming a data engineer? There is only one answer: yes!

What Is the Future of the Data Engineer?


Career Trajectory and Roles

Now, let’s look at the trajectory from an individual perspective.

At the entry level, the problems you need to solve as a data engineer are usually clearly defined. For instance, given an architecture, you may be asked to develop or code for some sub-module.

Imagine you have just joined an online cab booking company. You may be asked to create data structures to capture customer feedback.

But as you climb up the ladder, you have to study the product and define the business problems you think are the most important to solve. The solutions themselves also become increasingly ambiguous.

For example, say you have a limited budget allotted for cloud subscriptions and infrastructure your company uses. Given the demand for speed and functionality, what is the data engineering architecture you propose? What is the best use of your resources while also meeting the most important customer needs?

You can guess the answer may be subjective. It varies depending on the nature of the business and the situation.

What Is the Future of the Data Engineer?

As you get better and better at solving such problems, your responsibility grows as does your salary. With the right amount of skill and opportunity, you may even become a CTO someday!

Ready to Start Your Data Engineering Career?

Now that you’ve read this article, I hope you have enough confidence in the bright future of data engineering as a career.

As with any technology-related job, the skill sets needed for this field will surely evolve. Advanced hardware and sophisticated software are bound to change the way things are done today.

Always remember to stay abreast with the latest tech but don’t forget the basics, like understanding the needs of both internal and external customers and working backward to solve the problem. For hard skills, develop a solid command of SQL, coding in general (you may start with Python), and of course, data structures.

You and I are lucky to be living in an age where information and learning resources are available at our fingertips. So, why not exploit it with solid online courses?

Happy learning and all the best with your data engineering career!