Studying data engineering allows you to develop highly-demanded skills in multiple companies of different fields. Discover the job of a data engineer and why you should consider getting this education.  During the era of 5G, social media, Internet of Things, we generate more and more data. “Big Data” is a valuable asset for companies in all fields, which makes data analysis widely used.  Through analyzing the available data, companies are able to better understand the consumers’ expectations and take better approaches to stimulating their growth. The problem is that this process requires highly-qualified experts, and the demand for these experts is much higher than the supply. Nowadays, we are witnessing a real shortage of data science professionals. In this context, getting an education in data engineering allows you to develop highly-sought skills. You can, therefore, easily find a well rewarding job in a field of your choice.

What is data engineering?

In order to exploit data and reveal its real value, it is necessary to analyze it. This is the task of Data Scientists and Data analysts. Through the application of different tools and techniques, these professionals discover hidden trends and correlations between the data. Thus, their work bears fruit of precious information, which they present to the company executives in the form of visualizations and reports. Then, the organization can lean on this information while implementing better decisions, solving problems, or developing new products meeting the needs of their clients. However, to analyze data, it is necessary to collect it from numerous sources. Moreover, raw and unstructured data must be transformed, prepared, and cleaned in order to analyze it. This is what we call data engineering.

Data engineering, a key profession in data science

The role of a data engineer is to first of all, understand his employing company’s needs in terms of storage and computing architectures. He is in charge of putting in place a global data-exploitation strategy: acquisition, storage, transformation, production, etc…  The expert should build an automatic system dealing with the acquisition and treatment of streaming data through the construction of pipelines. He is also responsible of deploying Machine Learning models in production servers.  In summary, the role of a data engineer is to support analysts and Data Scientists. Thanks to his high-level work, the analysts and Data Scientists would just need to proceed to analyzing the data, which therefore, allows them to concentrate on discovering new exploitable information. Thus, the data engineer is should have an uninterrupted contact with Data Scientists and Data Analysts they should establish a good teamwork strategy in order to provide perfectly adapted solutions according to their needs. Over time, he must maintain the Big Data architecture and establish a technological support to keep it updated.

Why enroll in data engineering studies

Nowadays, the job of a data engineer is always highly-demanded by companies of all domains. Organizations are getting more and more data under their hands and they are well-aware of the value they present.  Big Data strategies are, slowly but surely, getting established. Data science teams are being formed, but Data Scientists and Data Analysts alone do are not sufficient. Data engineers are sought for to reinforce the latter’s ranks and take care of data prepping. Therefore, it is a very good career path to follow, for students as well as professionals in retraining phase. Data engineers are easily employed and their pay is generally attracting.  In France, the annual salary of a Data Scientist ranges between 45 000 to 50 000 €. According to the individual’s experience, the yearly salary may reach up to 60 000 €. However, this profession requires solid technical skills. Data engineers are obligated to master object-oriented development in Python, R, or Scala, diverse Big Data tools, IT infrastructure and application architectures. He must also be able to prep data and make data visualizations (Dataviz). The expert should also be able to understand his company’s specific issues; and have a certain level of knowledge about algorithms and machine learning. Getting a data engineering education allows you to build these skills. You can also learn to manipulate data via Python, understand the architecture of an OS such as Linux, choose and implement Machine Learning algorithms, or even develop Data Visualization graphs. As a conclusion, getting an education in data engineering allows you to develop cutting-edge skills, which are sought-for by businesses, which implies rapidly getting integrated in the job market and getting a highly-paid position. It is a flagship job in the data science domain, totally aiming for the future.