Why Has Data Engineering Become A Demanding Role In The Industry?

It won’t be wrong to term the 21st century as the ‘Data Era’, where the world tends to revolve around the four-letter word DATA. No single organization today can survive without data. But who is responsible for the collection and management of this data? You might guess a person who loves coding and data. Yet, it is simply not just the codes, but a job way beyond those. This is where the position of Data Engineering comes into the picture.

What exactly does a Data Engineer perform?

Data Engineer is involved in preparing data for analytical uses. These are the ones who develop, construct data, and maintain the detailed architecture of the large-scale processing system. However, the role varies from organization to organization. A typical data engineer would be involved in building a data pipeline to put all information together from sources. They then integrate, consolidate, and structure it for better analytical understanding.

Why is there a surging demand for more data engineers? 

With the rapid digital adoption owing to the coronavirus pandemic, there is a significant demand for technology-oriented jobs in the market. Concerning technology, data engineering is the fastest-growing job profile for every industry vertical and traditional industry to convert the unstructured data available in the market into a valuable asset for them.

While industries are trying to adapt to market changes, customers' behaviors, business insights, and artificial intelligence, the shortage of data engineer manpower has risen. The findings reinstate that companies took average 46 days to recruit for the role of data engineering.

How to match for a data engineering role? 

Data engineering has now become a desirable job profile amongst recruits. Big tech companies like Amazon and Facebook have given tremendous growth opportunities to data engineers. To be a part of this exciting profile, one must be a strong developer apart from having a master's degree in a technical related field. The knowledge of programming language is the basic core skill for this role. The data engineers should have extensive knowledge of creating bigger and more complex data products and must know big data technologies and APIs. 

The best strategy to excel in this field is to get into professional add-on courses and training sessions. Work on big data projects to gain experience and knowledge through practice.

How data engineering is different from other leading data roles?

Data engineering is different from the other two leading data roles of data analyst and data scientist. Most people have several misconceptions about these data roles. Let's clear them out here!

1. A data analyst is one who analyses all the numeric and other kinds of data and translates it in such a way that everyone can understand. So, the main responsibilities of the data analyst include data collection, correlation, and deporting. It is used by upper management to make informed business decisions. 
2. A data scientist is one who analyses and interprets complex digital data. For instance, statistics of the website. They deal with a large amount of structured as well as unstructured data and work mostly in statistics, programming, and machine learning to create strategic plans. 

Hence, by adding more skills and experience a data analyst can switch to the upper positions of data engineering. And the next milestone in data engineering is to become a data scientist. 

To sum up, data engineering is such a job in which you will never be working on the same thing for years, and ultimately takes a lifetime to master it which helps in upskilling data engineers for futuristic job profiles. There is no doubt this position requires a high level of skill and expertise in big data. And for this companies are scaling up hefty salaries for data engineers. 

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