All You Need to Know About Data Engineering

What is data engineering and how do I become one? In this blog, we talk about the ups and downs of data engineering to see whether or not you’ll fit the credentials of becoming a data engineer! Read on to find out more!

All You Need to Know About Data Engineering

What is Data Engineering?

Data engineering is the practice of designing and creating systems for storing and analyzing data. Data engineering is a broad field with many applications in a wide span of industries. They are the ones who pre-configure the data to be analyzed by data scientists and analysts.

Data engineers supplement machine learning and deep learning by processing and channel specific data.

Given vast amounts of data, especially in particularly large companies, this data will remain unreadable until data engineers work to build systems that make it readable.

Is Data Engineering a good career?

Data engineering, for one, is a high-paying career.

There is much demand for data engineers while the supply is astoundingly low. The average salary in the US spans around $111,933 - $164,000 per year (Glassdoor, 2021).

Money aside, data engineering is a great choice for people who have a keen eye for detail. Knowing yourself and your preferences about how data is intended to be used and building pipelines for it is a must.

A career in data engineering offers excellent earning potential and provides firm job security.

However, if you’re only in it for the money, it’s easy to lose passion and drive in this career choice.

This is what makes data engineering low in supply across the globe. People who fancy data aren’t necessarily available in abundance.

Where can I learn about Data Engineering online?

There is a handful of websites that offer data engineering classes; however, you cannot immediately become a data engineer after taking one or two courses.. It takes about a year to be able to functionally create and maintain systems and collect or report data.

Here is a list of websites that offer data engineering courses that are beginner friendly and systematic about building models, maintaining databases, supporting data analytics, and creating data plumbing.

  1. Code Academy – 14 lessons of beginner-friendly data engineering
  2. Udemy – Data engineering from design to implementation
  3. Coursera – Data engineering professional certificates
  4. EdX – Advanced data engineering courses

How do I become a Data Engineer?

While becoming a data engineer isn’t exactly entry-level, you can become a data engineer with the right amount of dedication.

Data engineers usually have undergraduate degrees in math, science, or even a business-related field.

It is very important that you know how to work with programming languages as a big chunk of being a data engineer comes with making use of various programming languages depending on the company’s preference.

While on the way to becoming a data engineer, it is necessary that you are able to fine-tune your analysis and data skills.

Acquiring data certifications is an advantage. Specifically, the most common undergraduate degrees that lead to becoming a data engineer are computer science, computer engineering, applied mathematics, and physics.

With the right amount of passion, you can be easily hired and acquire experience in data engineering as individuals with computer and information technology skills have been in high demand since 2020 and will continue to be so in the coming years.

Moreover, the rise of emerging technologies keeps us continually asking for more in the field of artificial intelligence and machine learning.

Can Data Engineering be automated?

To some extent, some areas of data engineering can be automated being associated with data science and artificial intelligence, in general. However, a big structure of data engineering cannot allow for AI algorithms to be the ones to build the infrastructure and analyze the data on their own.

While intelligent algorithms are capable of taking off the tasks that can be automated, some data are just too complex for AI to be able to read. Ultimately, the human touch and interpretation are still key to driving more value and accuracy.


Data engineering is not for everyone – especially those who are only after it for the pay.

There is a significant amount of effort and passion that you have to exert in building a dedicated data infrastructure and working with data scientists.

Having been experienced in many areas of computer science, data engineering can be a good career path for those who finished a similar undergraduate degree.

Will data engineering continue to be in demand in the coming years? Definitely!

The rise of technology, AI, and machine learning is basically telling companies that having a data engineer is a must, rather than just a mere option.

Data engineering will definitely keep going in the decades to come and will continue to be the vanguard of data infrastructures and data pipelines for data scientists and data analysts to read and understand.

Read more about why data engineers are an invaluable asset in a team in this blog.