Job profile:
Data Engineer (m/f/d)
Data is considered the "gold of the 21st century". In a world in which this data is generated in incredible quantities, it is necessary to organize and maintain this amount of data. Data engineers are needed in large companies for this often complex task.
Find out here what skills a data engineer needs to have, what salary can be expected and what the differences are to other big data jobs, such as data scientist.
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What is a data engineer? Definition and tasks
In the course of digitalization, the need for qualified IT specialists is constantly growing in data-driven organizations. They collect the most important "raw material" of the 21st century, process it and then evaluate it. The data engineer therefore provides (large) companies with what may be their most important asset: data.
Data engineers (also known as data technicians) use a wide range of technological options and tools to provide their companies with this important information. This enables them to generate, store and process large volumes of data. The processed data is then summarized in an analysis infrastructure for the next work process and transmitted to the responsible persons.
The opportunities on the job market are extremely good, as data engineers are needed wherever a lot of data is generated. In addition to companies in the field of information technology, organizations from a wide range of specialist areas such as healthcare, engineering, automotive, e-commerce, finance, banking and insurance are also looking for well-trained data engineers.
Data Engineer Salary: A comprehensive overview
The Hays IT Salary Report (German only) shows:
Depending on career level, company size and location, Data Engineers earn an average of €69,800 per year. Salaries are above average, particularly in major German cities. They are highest in Hessen. 38% of employees in the data sector are satisfied with their earnings, 75% are willing to change jobs.
Starting salary Data Engineer: What Junior Data Engineers earn
Even as a beginner, you are already one of the higher earners in this profession: as a junior data engineer, you can expect a starting salary of between €44,700 and €54,300 per year. In smaller companies, the salary may also be lower. The industry is also decisive - in the automotive sector you can expect the highest starting salary of €54,000 and more. Starting salaries are lowest in the retail sector.
Most employers require a Master's degree for this job, which means that Bachelor's graduates can generally expect a lower starting salary.
Starting salary Data Engineer: What Junior Data Engineers earn
Even as a beginner, you are already one of the higher earners in this profession: as a junior data engineer, you can expect a starting salary of between €44,700 and €54,300 per year. In smaller companies, the salary may also be lower. The industry is also decisive - in the automotive sector you can expect the highest starting salary of €54,000 and more. Starting salaries are lowest in the retail sector.
Most employers require a Master's degree for this job, which means that Bachelor's graduates can generally expect a lower starting salary.
Starting salary Data Engineer: What Junior Data Engineers earn
Even as a beginner, you are already one of the higher earners in this profession: as a junior data engineer, you can expect a starting salary of between €44,700 and €54,300 per year. In smaller companies, the salary may also be lower. The industry is also decisive - in the automotive sector you can expect the highest starting salary of €54,000 and more. Starting salaries are lowest in the retail sector.
Most employers require a Master's degree for this job, which means that Bachelor's graduates can generally expect a lower starting salary.
Senior Data Engineer salary: what experienced specialists earn
Your earning potential will also increase as your experience grows. As a Senior Data Engineer, you will earn between € 68,000 and € 84,000. Here too, the location and size of the company play an important role. As a manager, you can also expect salaries of up to €103,000 in this profession.
Big Data Engineer: Salary
You can also expect similar salary ranges in the Big Data sector. At the beginning, you can expect to earn around €52,000, which can improve in leaps and bounds after just a few years.
How do you become a data engineer? Training, studies & further education
There are various ways to start a career as a data engineer: for example, by studying or by making a career change. A critical examination of your own skills and prior knowledge is an important first step here.
A university degree in STEM (science, technology, engineering and mathematics) courses is a good starting point for tackling the further extensive learning process and building up the know-how that may be lacking.
It is particularly important for prospective data engineers to understand ETL (extract, transform, load), i.e. the data cleansing process and the correct use of common tools such as Python.
Data Engineer training
There is (still) no standardized training for data engineers. The job is therefore a classic career changer. Although a degree in this field is welcome and is definitely an advantage when looking for a job, trained specialists in (business) informatics and computer technology or statistics are also among the attractive candidates for jobs in data engineering.
After graduating, you have a wide range of further training courses to choose from. Depending on the course, you can learn the basics of programming, big data, databases and automation.
There is (still) no standardized training for data engineers. The job is therefore a classic career changer. Although a degree in this field is welcome and is definitely an advantage when looking for a job, trained specialists in (business) informatics and computer technology or statistics are also among the attractive candidates for jobs in data engineering.
After graduating, you have a wide range of further training courses to choose from. Depending on the course, you can learn the basics of programming, big data, databases and automation.
Data Engineer studies
Although data engineering is not a traditional field of study, some faculties now offer a degree course in it. At the Technical University of Munich, for example, it is possible to complete a Master's degree in "Data Engineering and Analytics".
For studies of this type, an aptitude test is usually required to check the skills and knowledge of the candidates.
Apart from that, there are numerous fields of study that make it easier to enter the world of big data: Business informatics, computer science, data management, computer engineering or statistics are among the classics. Students in these subject areas already learn a large part of the theory and skills required for a career in data engineering.
Although data engineering is not a traditional field of study, some faculties now offer a degree course in it. At the Technical University of Munich, for example, it is possible to complete a Master's degree in "Data Engineering and Analytics".
For studies of this type, an aptitude test is usually required to check the skills and knowledge of the candidates.
Apart from that, there are numerous fields of study that make it easier to enter the world of big data: Business informatics, computer science, data management, computer engineering or statistics are among the classics. Students in these subject areas already learn a large part of the theory and skills required for a career in data engineering.
Data Engineer: lateral entry as a classic route
As there is no traditional degree course for a career in this field, data engineers are usually typical career changers. After studying IT or statistics, various further training courses are a good way to embark on this career path.
Interested individuals can choose from a variety of different learning formats and course content and decide whether they want to start on a fixed date or prefer to learn in a self-determined and flexible way - there is a wide range of offers from providers such as the IHK or the IU Academy.
It is not only female career changers with a degree who currently have immense opportunities to embark on a promising career in this field. Even if you have a degree in statistics, the demand is there and you can gain further qualifications as a data engineer according to the "learning on the job" principle. Various providers also offer further training in this area.
As there is no traditional degree course for a career in this field, data engineers are usually typical career changers. After studying IT or statistics, various further training courses are a good way to embark on this career path.
Interested individuals can choose from a variety of different learning formats and course content and decide whether they want to start on a fixed date or prefer to learn in a self-determined and flexible way - there is a wide range of offers from providers such as the IHK or the IU Academy.
It is not only female career changers with a degree who currently have immense opportunities to embark on a promising career in this field. Even if you have a degree in statistics, the demand is there and you can gain further qualifications as a data engineer according to the "learning on the job" principle. Various providers also offer further training in this area.
Data Engineer: further education and training opportunities
Due to the high demand for qualified specialists, there are a large number of further training courses for data engineers on the market. These include further training courses on topics such as cloud computing, programming languages and automation. As a data engineer, you also have the right qualifications for further training or retraining as a data analyst.
Other helpful training courses will certify you in big data technologies such as Hadoop, Spark or Apache Kafka, which is popular with employers.
Due to the high demand for qualified specialists, there are a large number of further training courses for data engineers on the market. These include further training courses on topics such as cloud computing, programming languages and automation. As a data engineer, you also have the right qualifications for further training or retraining as a data analyst.
Other helpful training courses will certify you in big data technologies such as Hadoop, Spark or Apache Kafka, which is popular with employers.
Data Engineer tasks: What does a data engineer do?
For these tasks, the data engineer uses a variety of different technologies and tools, such as:
- Big data technologies such as Hadoop, Apache Spark and other No-SQL databases (i.e. non-relational databases),
Cloud technologies such as AWS (Amazon Web Services) or GCE (Google Compute Engine),
relational databases or
ETL (extract, transform, load) tools
Data engineers work at the interface between hardware and data processing. They adapt algorithms and tools according to their project requirements and thus continuously generate important data. They are also responsible for setting up and monitoring the IT infrastructure as well as managing and securing the data.
Their work forms the basis for data science activities and enables the professional use of data. Using data pipelines - a series of data processing elements - they ensure an automatic flow of data. For example, the data ends up in a so-called data warehouse, a central repository where an organization's data from various sources is stored.
The difference to the Big Data Engineer
Data engineers are sometimes also referred to as cloud data engineers or big data engineers. The terms refer to the same activity with different nuances. Big data involves huge amounts of data. The distinction between the two role designations is therefore primarily about the amount of data. In many cases, they also differ in the tools they use for their work.Data Engineer vs. Data Scientist: A comparison
While the world of the data engineer revolves around the standardization of data, data scientists master the interpretation of data chaos.
Data engineers are responsible for the development, maintenance and optimization of data infrastructure and pipelines and collect and process data. The data they collect is stored in various formats, databases or text files.
Data scientists are experts in data analysis. Using measures such as tracking or monitoring, they generate a structured database from raw data. With their business know-how, they create the basis for recommendations for action or decisions and thus answer important questions in their industry based on data. This is how big data becomes smart data.
Data scientists develop and improve methods for analyzing data that are used to collect data on company-relevant issues. They have experience in mathematics, especially in statistics and stochastics, machine learning and data visualization and are proficient in programming languages such as Phyton, Julia, R or SQL. Strong communication skills are required in order to present the data obtained and the resulting recommendations for action to the relevant specialist departments.
Both roles work closely together: While the data engineer receives, stores and organizes the data, the data scientist gets ready to examine it. In some cases, the data scientist then hands over the results to the data analyst for in-depth analysis.
Data engineering skills: These skills are in demand
Data engineers have a wide range of technical skills that are indispensable in this job. However, their soft skills are also in demand on an interpersonal level: they regularly interact with people from other departments and customers in their day-to-day work. They therefore need strong communication skills in order to solve problems in a team and ultimately lead projects to success.
They should also motivate other employees with their hands-on mentality and proactively look for solutions and optimizations when systems and data processes do not work as intended.
In summary, Data Engineers should have the following technical and soft skills to perform their tasks efficiently and effectively:
- Technical understanding of big data infrastructures and technologies: This includes languages such as SQL
- Knowledge of software, programming languages and machine learning
- Excellent database skills
- Understanding the ELT process: A method that stands for Extract, Transform, Load and is used for large data pools and in the cloud area
- Analytical skills
- Communication skills for the presentation of analysis results
- Good knowledge on the subject of data protection
- Certificates in Big Data technologies such as Hadoop, Spark or Apache Kafka are an advantage
Data Engineer: Opportunities on the job market
As the demand for female data technicians has increased immensely in recent years, the opportunities on the job market for big data are very good.
These specialists are needed across all sectors in many companies that come into contact with Industry 4.0, IoT (Internet of Things) or the customer journey. Engineers from mechanical engineering, the automotive sector or the chemical industry who have opted for big data are therefore particularly in demand.
In principle, talented data engineers are in demand in all large companies that have to cope with and manage a large amount of data. This can also be the case in e-commerce or marketing, for example.
Your salary prospects in this job are also above average and there is no sign of demand leveling off any time soon.
Top vacancies: Data Engineer Jobs (m/f/d)
FAQ
A data engineer in Germany earns an average of € 69,800 gross per year. The starting salary is also impressive and is around €50,000. The level of salary depends heavily on the level of experience, location and industry of the company. Due to the high demand, data engineer salaries are above average.
A data engineer in Germany earns an average of € 69,800 gross per year. The starting salary is also impressive and is around €50,000. The level of salary depends heavily on the level of experience, location and industry of the company. Due to the high demand, data engineer salaries are above average.
For a career as a data engineer, it is advisable to complete a Master's degree in a STEM (science, technology, engineering and mathematics) program and to acquire additional technical skills through further training. With this knowledge and skills, entering the world of data engineering should not be a problem.
For a career as a data engineer, it is advisable to complete a Master's degree in a STEM (science, technology, engineering and mathematics) program and to acquire additional technical skills through further training. With this knowledge and skills, entering the world of data engineering should not be a problem.
The salaries of a Data Scientist and a Data Engineer are very similar: both roles earn an average of €69,800 in Germany.
Data engineers take care of the large amounts of data that end up in a company in different ways. Their task is to process this data with the help of ETL tools (extract, transform, load) and make it available for further analysis.
There is no specialized course of study to become a data engineer. As a rule, data engineers are IT or statistics specialists who are venturing into this career field. A Master's degree in a relevant field is generally recommended to work as a data engineer.