what is a data engineer?

Data is being generated in larger quantities and at a faster pace than ever before all over the world. The total volume of data from both private and professional contexts is expected to reach 175 zettabytes (ZB) in 2025. That is an increase of 130ZB since 2019. What is driving the enormous growth of data is the growth that has taken place in other areas, including communication in the digital sphere. The emergence of digital companies and digital business, as a result of the pandemic, is also a big part of the explanation for the enormous increase in data volume.

With so many ones and zeros stored on different servers and storage devices all over the world, how can society and the market make the best use of the enormous volume of information that has been collected? And who can help to interpret and use the information in the most effective way?

As organisations and companies across much of the world focus more on a digital workflow, there is also a growing need for employees who help ensure that the information collected as data is actually processed, cleaned, and formatted in a way that makes it manageable. This is so that the companies' data scientists can use it to improve the business. In fact, both data scientists and data engineers are important players on the same team, with the goal of converting all these ones and zeros into usable information that helps business leaders make more well-founded, smart, and effective decisions.

The need for these competent people will remain high, completely in line with the focus on digital entrepreneurship that now characterises the whole society. According to a survey conducted at the beginning of the fourth quarter of 2020, there were globally over 150,000 open positions for data engineer on LinkedIn.

data engineer jobs
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average salary as a computer engineer.

That there is a great need for data engineers and other competent roles related to data analysis is obvious, considering how society as a whole has developed in recent years. The significant digitalisation has increased the need for data engineers, which means that someone who is trained as a data engineer or has the right skills to take on the role is in a good position when it comes to salary negotiations. At the same time, data engineer is a role that many employers need to fill and that can be designed in many different ways. That is one of the reasons why it is not easy to point out what the average salary looks like for someone working as a data engineer.

factors that influence the salary as a data engineer.

A data engineer can have many different tasks. This in itself means that the complexity of the role can vary, and the requirements for someone working as a data engineer therefore look different depending on who the employer is. A more complex, responsible role as a data engineer will give you a better position for negotiation. In such cases, the salary is generally higher.

At the same time, data engineer is a job that is needed in many sectors and is not only linked to pure IT companies. Many other large companies and organisations need data engineers in their daily operations, to learn how to interpret all the data and information available. That is another factor that affects the salary as a data engineer. The general salary level is higher in certain sectors of the labour market. Therefore, the choice of employer has a big impact on the salary you get as a data engineer.

Randstad
Randstad
2

what is a data engineer?

The general view of a data engineer is that it is a profession that involves collecting, organising, and managing data. Someone working as a data engineer is an important part of the work around handling data, by creating an architecture that will collect, utilise, and process the available data. The goal is to prepare the data for data scientists, who will then analyse the information and draw various conclusions with the help of the information. A data engineer is tasked with identifying trends in datasets and developing algorithms that are an important part of preparing the data. Just like for many others in the IT field, it is required that, as a data engineer, you have deep and specific technical knowledge, such as being able to use different programming languages, work with cloud services, and have knowledge of SQL databases.

But it's not only technical knowledge that's important in the role of data engineer. As a data engineer, you're also part of a bigger team or department that needs to deliver important analyses and insights that company management needs in order to set both short- and long-term goals for the business. By helping management to quickly and efficiently understand and relate to trends that have become clear when interpreting the data, the analytics department in a company can play an important role for the entire growth of the company.

A recurring task for a data engineer is to work together with other IT colleagues to develop the architecture and interfaces that make the data more useful in the business. This can involve preparing the information to be imported into various databases, and the person working as a data engineer is responsible for ensuring that the data is handled in a secure way that does not violate privacy. Other common tasks include combining different datasets, deciding how information should be stored, and working together with data scientists and data analysts to draw important conclusions from the data that has been collected.

In general, you can say that data engineers are often one of the following: generalists, workflow-focused, or database-centered. As a generalist, you can be involved in all data-related tasks within the company, including the analytics part. Someone who is more focused on the workflow works with the data flow within the organisation, while a database-centered data engineer manages several different databases. The size of the company or organisation determines which type of data engineer is needed in the business. In many smaller companies, it is a smaller team or a single data engineer who has to handle all the data. In larger companies, you can hire several different data engineers, who can then be specialised in different areas.

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working as a computer engineer.

A data engineer can have different tasks depending on which employer you work for. But there are some common tasks that come up in the job. Read on to find out more about what a typical workday looks like and how to apply for an open position as a data engineer.

male looking at a tablet standing in a servers room.
male looking at a tablet standing in a servers room.
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education and qualifications as a data engineer.

To become a successful data engineer, it is advantageous to have knowledge in programming, mathematics, software development, data analysis, database management, IT and cybersecurity. Having a strong technical background gives you a solid foundation if you plan to work as a data engineer, regardless of which type of data engineer you want to become. Many organisations and companies looking to hire data engineers are searching for candidates with an academic degree in one of the following areas:

  • IT
  • computer science
  • software engineering
  • mathematics

Besides academic merits, there are other qualifications that can be advantageous for a data engineer. At the same time, you should keep in mind that qualification requirements look different at various employers, depending on how the role is structured and which skills are needed. But there are a number of certifications that can be relevant on a global level, among other things. Some examples of qualifications are:

  • Amazon Web Services (AWS) Certified Data Analytics – Specialty
  • Cloudera Certified Associate (CCA) Spark and Hadoop Developer
  • Cloudera Certified Professional (CCP): Data Engineer
  • Data Science Council of America (DASCA) Associate Big Data Engineer
  • Data Science Council of America (DASCA) Senior Big Data Engineer
  • Google Professional Data Engineer
  • IBM Certified Data Architect – Big Data
  • IBM Certified Data Engineer – Big Data
  • SAS Certified Big Data Professional
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skills and competences.

Data engineers need to have basic technical knowledge, but possess deep knowledge in data architecture and design, management as well as maintenance of databases. Good knowledge of many programming languages and different digital tools is required. It is the employer and the design of the role that specify which skills are needed, but some important tools to be familiar with can be:

  • apache spark
  • SQL
  • hadoop
  • beam
  • java
  • python
  • R
  • kafka
  • extract/transform/load (ETL)
  • amazon web services
  • databases
  • shell scripting
  • distributed ML platforms: MLib (Spark)
  • parallel computing for deep learning (Tensorflow, GPU Programming)
  • development in containers (Docker, Rkt)
  • programming in notebooks (Zeppelin, Jupyter)
  • java, C++, and/or Go and functional languages (Scala, Clojure,Elixir)

There are also soft values and qualities that can be useful in the role of data engineer. Being a skilled communicator, a good team player and good at planning as well as organising your time are important qualities for those who want to succeed in the role of data engineer.

Randstad
Randstad
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FAQs.

frequently asked questions about working as a data engineer.