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Data is one of the biggest buzzwords these days. While data science has emerged as one of the most popular fields of study and for work, data engineering is, comparatively, a silent sibling that has witnessed a meteoric rise. But, what is data engineering, how it’s different from data science, what do data engineers do? Read on to get these answers!

What is Data Engineering

What is Data Engineering?

To understand what  data engineering is, let’s break it down into two parts: Data + Engineering. The secret lies in the second part i.e. engineering. Like engineering — which is concerned with building — data engineering is to design and build data pipelines. These pipelines act as a source of truth as they take data from various sources and then collect them in a single source.

Easier said than done, it requires a lot of skills. In fact, this is the reason why demand for data engineers has been exceeding the supply since 2016. The Dice 2020 Tech Job Report called data engineer  the fastest growing job in technology in 2019, with the number of open positions growing at a rate of 50% Y-o-Y. 

The Data Engineering vs Data Science Conundrum

Some people love beaches but still visit mountains sometimes, some love mountains but still visit beaches sometimes. Similarly, all data engineers do some analytics and all data scientists do some programming. 

Additionally, apart from the tech skills data science requires more knowledge of statistics and ETL (Extraction, Transformation, and Loading) while data engineering requires more Agile skills.

Consider this, there is a race car builder and a race car driver. The race car driver gets all the limelight, the thrill, and the real experience of sitting in a race car but a race car builder enjoys designing the car, experimenting with the various parts, and setting it up for the race track. If you connect more with the latter then data engineering is for you.

The Changing Role of Data Engineers

The role of data engineers is fast changing, especially because the tools and modules used by them have evolved exponentially over the last few years. But, this doesn’t mean that the role is getting simplified. It only means that new skills are now required to excel in the field. In fact, there are some early signs of new disciplines. For example, Analytics Engineering is already a thing.

Professionals have identified the following gaps in recent times which hinder the transition to advanced tools and methodologies:

  • Version control and understanding of CI/CD pipelines
  • Knowledge about the modern cloud data analytics stack
  • Learn more programming languages, SQL isn’t enough

While all of these points are true, remember that it is an evolving discipline and different companies need different skills. You just need to prepare right!

Prepare for the Hottest Job Now!

So now you know what  data engineering is and have a fair idea about what to expect as a data engineer

Check out Udacity’s Data Engineering Nanodegree program and learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. By the end of the program, you’ll be all set for a full-fledged career in data engineering.