How do I learn data engineering
What does a data engineer do? Overview of the job description
A data engineer deals with the collation, preparation and checking of data. The activity forms the basis for big data, data warehouse and analysis projects in the context of data science. Data engineers are important job profiles in any data-driven organization.
Let's jump in:
- Data engineer job description
- What skills does a data engineer need?
- What are the tasks of a data engineer?
- What does a data engineer earn?
- The data engineer training
- Data engineer vs. data scientist
- Data Engineer vs. Machine Learning Engineer
Data engineer job description
The professional field of data engineering deals with the collation, processing and checking of data. The activity forms the basis for analysis projects in the context of data science projects and when dealing with big data. A data engineer (or data technician in German) models and scales databases and thus ensures the flow of data within a company. For this task, the data technician uses a wide range of tools and technologies:
- Relational databases
- ETL tools
- Big data technologies (Apache Spark, Hadoop or other no-SQL databases)
- Cloud technologies like AWS S3
As more and more companies are relying on cloud solutions, setting up and configuring the cloud is also one of the core topics of data engineering.
The specialists can choose their industry almost completely freely - because topics such as Industry 4.0, IoT - Internet of Things - or the digitization of the customer journey affect almost all companies.
There are currently many vacancies, for example in mechanical and plant engineering, the automotive industry or the chemical industry. But data technicians are also increasingly in demand in public administration and marketing.
What skills does a data engineer need?
A data technician must have extensive knowledge in the field of data processing —————- n. In addition to in-depth knowledge of the requirements of a data process, a data technician should also have advanced knowledge of programming. Because it happens again and again in everyday work that existing algorithms have to be revised, adapted or newly developed.
In addition to technical knowledge, a data technician should also have soft skills in the area of interpersonal communication, because daily contact with non-specialist people from different departments is part of the job. That is why a data technician should be able to reproduce complicated technical issues as simply as possible and in a way that is understandable for laypeople.
Summarized you can say that a data technician Understanding of mathematical, physical and technical processes must have. In addition, should interest at the optimization of infrastructures.
What are the tasks of a data engineer?
Data specialists have to solve a wide variety of tasks in their everyday work. A data engineer takes care of all processes related to the creation, storage and maintenance of data sets. An important core aspect is the preparation and transfer of data, the so-called handling. The construction and monitoring of IT infrastructure is also one of the tasks of a data technician.
Depending on the company, concepts, purchasing and setting up hardware components and the selection of the optimal software may be required here.
Data Engineer Interface between hardware and data processing
The data technician works at the interface between hardware and data processing. As part of the job, data sources are monitored and the instances that are responsible for the analysis and further use of the data generated in the area Big dataare responsible, managed. Furthermore, the data engineer optimizes existing algorithms or uses special tools to optimize internal data analysis or existing databases.
Last but not least, in many companies the data technician is responsible for the security and reliability of the entire IT system. Therefore, in-depth knowledge of data security and data protection is required in the professional field.
What does a data engineer earn?
The more data is processed within a company, the more people are looking for specialists with the relevant knowledge. That is why prospective data engineers can look forward to high entry-level salaries. That's the way it is Starting salary on average at already 50,000 euros in the year!
Here you can find an up-to-date source on the salary development.
With increasing experience can be up to 70,000 euros annually to earn. Especially in the German IT clusters such as Munich, Hamburg or Berlin, salaries can still be well above the average.
However, if you want to add a shovel of salary, you should look for jobs in the Data engineering in the USA look around. Here, significantly more is paid for the job, at the same time the tax burden is lower. But in Europe too, the data technician is one of the best-paid and most sought-after professions on the market.
The data engineer training
Unfortunately, there is currently no option in Germany to take data engineering as a separate course of study. However, since the demand for data specialists has risen rapidly in recent years, the data engineer represents the classic lateral entrant. The current specialists mostly come from the fields of information technology, business informatics or computer technology.
It is also possible to train as a data technician after completing a statistical training. If you want to qualify as a data engineer, you should definitely be prepared to familiarize yourself with existing data projects - learning on the job is the motto!
By the way: It is not only with a degree that you get the qualifications you need! Rather, data technicians who have completed training in the IT area are considered real practitioners - and are accordingly in demand!
Data engineer vs. data scientist
Often these two very different areas of activity are confused or not clearly defined in job descriptions. In consulting projects, too, it often happens that data science skills are advertised, but data engineering skills are required. This can lead to major problems and dissatisfaction, as those affected have completely different skills.
From practice (countless data science and big data / data engineering projects) I have learned that the teams work particularly well when the roles are clearly defined.
Data Engineer vs. Machine Learning Engineer
A data engineer is often confused with a machine learning engineer. A machine learning engineer has more of a software development background and is primarily responsible for the operationalization and maintenance of machine learning models. Here, it is tracked whether the models still have the appropriate quality or whether they have to be trained again.
The machine learning engineer job description is still relatively new, but due to the rapid progress in the field of artificial intelligence and machine learning, this job is becoming more and more important.
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