As a Data Engineer, you help your company cope with the vast amounts of data that are generated every day as a result of big data. Your task is to prepare and store the unstructured information so that it is available for further analysis.
What are the tasks?
The Data Engineer ensures that Business Analysts or Data Scientists are provided with the necessary data they need for their tasks. This will require various types of tasks. These include, for example:
- The right data sets must be found in order to be able to implement the requirements from the business side.
- The data engineer develops algorithms to prepare and cleanse the source data so that other data scientists can easily use it.
- ETL – pipelines that procure data from source systems, prepare it, and deposit it into a target database must not only be created but also constantly tested for functionality.
- All of these tasks must also ensure that data governance concepts are adhered to so that all users have the necessary permissions.
In many cases, data engineers work closely in a team with data scientists, who can then convert the data provided into analyses or machine learning models. In such circumstances, it can also happen that tasks of data scientists, such as the creation of analyses, are also taken over.
In which industries do Data Engineers work?
Nowadays, there are no longer certain industries in which data engineers are increasingly working, since large amounts of data are generated in almost all companies, these skills are also needed almost everywhere. Thus, the position of data engineer offers the advantage to choose the industry according to personal interests.
In industry or the automotive sector, a lot of technical data is generated, for example from production or from sensors on the finished product. The main focus here is on the early detection of faults, for example, whether a machine is overheating or producing poor-quality parts.
In retail and e-commerce companies, however, the focus is completely different. The main goal of data storage is to better understand the customer and thus better tailor the respective product portfolio to the customer. In e-commerce, for example, it could be relevant to evaluate the customer journeys in order to recognize how the customer moves through the website.
One last big industry is banks and insurance companies. Large amounts of data are generated about customers, which must be made available to the data scientists and offer their own technical challenges.
What skills should you bring with you?
As a data engineer, you are primarily concerned with data storage and provision. Therefore, you should have sufficient knowledge in the area of databases and data architectures or the ambition to quickly familiarize yourself with these topics.
This includes being able to weigh up the advantages and disadvantages of data lakes and data warehouses and choose the right data architecture depending on the use case. In addition, you should know the state-of-the-art databases that are already used by many companies and, if possible, be able to implement them independently.
Similarly, important are skills in the area of common ETL tools, so that the data finds its way from the source systems into your data architecture and is also transferred into the target format along the way.
To be able to implement all these tasks and skills, basic programming skills in Python and SQL are essential for a data engineer. In many cases, these are the most common languages when working with databases or ETL tools and will therefore become your daily companion.
Depending on the position you want to apply for, skills from the area of a business analyst or data scientist are of course a plus. In reality, the applications will probably also often overlap and a clear separation will be difficult. Thus, initial knowledge of the use of business intelligence tools and machine learning are definitely an advantage in your application.
Training and Study
There are many courses of study that are helpful to starting a career as a data engineer. It is important that you already come into contact with programming in this subject and learn to create algorithms. If possible, you will also learn about the common tools in the field of big data and databases during your studies.
As a prospective data engineer, bachelor’s degrees in computer science, mathematics, physics, or data science are conceivable. However, as with many other jobs in the field of data science, the current demand for good specialists is so great that many companies also welcome career changers.
This is what you should take with you
- A data engineer ensures that the large volumes of data in a company are processed and stored in a targeted manner.
- They are responsible for the proper functioning of ETL pipelines, compliance with data security guidelines, and deciding on the appropriate data architecture.
- Indispensable skills for data engineers are knowledge of data architecture and databases, as well as basic programming skills in Python and SQL languages.
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