December 17, 2021
jeg empty 11 - What Is Modern Data Engineering?

Currently, there are 6,500 people on LinkedIn with the title of data engineer, 50% of whom live in the US. Companies’ demand for these specialists is much greater than the number of people in the labor market. Just in San Francisco are 6,600 free vacancies with the same title. Data engineers have doubled over the past year, but digital leaders face a significant talent shortage. So who is a data engineer, and why are current data engineering services so desirable?

Unicorns (companies valued at over a billion dollars, such as Google or Apple), in which data is the company’s fuel, use data engineering in their activities. It is among their structures that we find the most data engineers. In Europe, this profession is not so popular yet, although the demand for engineers in cities where startups thrive, such as Berlin, is more noticeable. But let’s be honest. The success of today’s businesses depends on data. However, it is not just about obtaining data – obtaining data is one thing, but effectively managing it is another. Companies successful in artificial intelligence typically rely on engineering expertise in modern data engineering. Before we describe this type of service, let’s take a closer look at why businesses require big data.

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The importance of data in business

Data quality assurance is often a guarantee of effective sales and loyalty initiatives, commercial strategy, and any marketing project. Data is also the fuel for any analytical application and business operation. Moreover, businesses that use the correct data can manage risk effectively. These companies react much faster and flexibly to changes in their market. As a result, they can act quickly in the event of threats and thus avoid big strategic mistakes, thus reducing costs and minimizing losses.

Investing in data management solutions is a matter of course for many companies. It does not just have data that counts. You can’t effectively use incomplete, inaccurate, or even inaccessible information. The weight of data relies mainly on its quality; that is why the demand for specialists in data engineering is growing.

Data Engineer: Definition

Data engineering is the science of gathering and verifying information (data) so that data scientists can use it. The data analysts are liable for interpreting data and utilizing it for various purposes. However, they need good-quality data to accomplish complex tasks like forecasting business trends. That is where data engineers come in.

Here you can find more information about data engineering: https://addepto.com/data-engineering-services/

The role of data engineering

The role of the data engineer is essential because it is associated with the delivery, storage, and processing of data. Therefore, the main task of engineers is to provide a reliable infrastructure for data. Data engineers, also known as data architects or data infrastructure specialists, are responsible for building the infrastructure on which data analysis projects are later based. Data engineers are tasked with collecting and processing raw data, assessing the usefulness of new information sources, and designing and launching new relational databases, allowing for the storage and processing of information flowing into the system. That usually involves the implementation of data pipelines. In creating this information architecture, data engineers rely on various programming and data management tools to manage relational and non-relational databases and build data warehouses.

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Modern data engineering is changing the face of this profession

With the source of big data, the spectrum of responsibilities and tasks has transformed dramatically. Previously, these engineers wrote large SQL queries and kept ahead of the data with tools such as Informatica ETL, Pentaho ETL, Talend. Today, however, the demands placed on data engineers have increased. As a result, most of the companies holding vacancies for the position of Data Engineers have the following requirements:

  • Superior learning of SQL and Python
  • Knowledge about cloud platforms, specific, Amazon Web Services
  • Understanding of Java / Scala
  • A good acquaintance of SQL and NoSQL databases (data storage, data modeling)

It is worth considering that this is only a tiny part of a data engineer’s most basic duties. Now, Data Engineers are also experts in backend and software development. For illustration, if a company begins to generate extensive quantities of data from numerous sources, the data engineer’s job is to manage the information gathering, processing, and storage.

Data engineering has visibly evolved towards big data in recent years, particularly in processing under heavy loads. Moreover, companies are also increasing requirements for system resilience to failures. Thus, the market for data engineering assistance is constantly growing and is practically catching up with data analytics.

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Data engineering and data analytics

Now that you know what data engineering does and who data engineers are, it’s also worth the difference between this field and data science. These two concepts are often confused. There is much ambiguity between a data scientist and a data engineer; therefore, it is sometimes difficult to distinguish one profession from another. Some skills are required for both positions. However, there are several opposing skills. For instance, the data engineer comprehends programming more competently than any data scientist, but it could be the precise contrary regarding statistics. On the other hand, a data analyst needs data engineering to properly prepare the data to use data flows and integrated data structures.

Does my company need data engineering?

Data surrounds us. Organizations can use data engineering for various purposes, including customer service, market research, and of course, sales. As a result, building sophisticated data systems becomes indispensable in the operation of companies. First of all, hiring a data engineering expert is necessary when:

  • The company has a product that is entirely cloud-based and, therefore, data-driven
  • The company has a need or a desire to analyze a large amount of data

Of course, considering the current shortage of data engineering specialists on the market, not every company will have the opportunity to hire an expert. Moreover, not every company will need a data engineer in its structures. Therefore enterprises increasingly turn to data engineering consulting experts to organize the system and use the data to improve business outcomes, and it can be a good solution for you that helps you develop your company and increase profits.

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