What does a Data Engineer actually do at DB CargoLab?

When Sanja Klein looks at the endless rows of data, she doesn't just see numbers - she sees possibilities. As a data engineer, she is the unseen force behind the scenes that ensures that a wealth of raw data is turned into precise and usable information. The DB CargoLab's Asset Intelligence Center is where the big data streams come together: Sanja Klein and her colleagues are responsible for collecting, cleansing, processing and managing it. 

Paving the way for data-driven decisions

With her inputs, Sanja Klein helps to ensure that decisions at DB Cargo can be made on the basis of data, as she works with data scientists and experts to ensure that the data is prepared for analyses and machine learning models. This not only drives the digitalization and automation of processes, but also increases service quality and reduces the ecological footprint. The Data Engineer's task therefore also plays a key role in the implementation of DB Cargo's vision for automation and digitalization in production "Intelligent Rail Freight Transport System 2030+". The vision maps the development of rail freight transport along the value chain up to 2030 and beyond and is implemented in the form of innovation projects in the DB CargoLab.
 

Profile: Sanja Klein 

Sanja Klein

That`s how I came to DB Cargo: 
I completed my master's degree in psychology and then went on to do my doctorate in the field of imaging neuroscience. In my scientific work, I was already confronted with processing large amounts of data, complex analyses and special challenges in terms of data protection. I realized that I enjoy these topics just as much as my love of science and therefore decided to continue my professional development in this field after completing my doctorate.

You should have these qualities for my job:
For inputs as a Data Engineer at DB CargoLab, analytical thinking and problem-solving skills are just as essential as sound programming knowledge, especially in Python and SQL. A good understanding of data types and data paths, coupled with the ability to work in a team, strong communication skills, a willingness to learn and openness to new technologies are also of great importance.

I like to do that in my free time: 
I like to pursue creative hobbies, such as knitting or cooking, and I also listen to a lot of music and podcasts. I'm particularly interested in the latest news from the tech scene and the interactions between technology and people. Of course, sport is also a must when you spend all day at your desk.

Passion for data and constant challenges

In her role as a data engineer, Sanja Klein pursues her passion for solving complex problems and developing efficient data solutions every day. Together with her team, she strives to keep her finger on the pulse and apply the latest methods. "This means there are always new challenges and there is never a dull moment," says Sanja Klein. A particular project highlight was working on a machine analysis to automatically detect damage to freight cars using photos taken from camera bridges at classification yards. She also worked on an intelligent solution for feeding damaged wagons to workshops based on mathematical optimization methods.

An optimistic view of the future

The necessary digitalization and automation measures for a successful future in rail freight transport are leading to an increasing demand for quality-assured data. Data-driven solutions offer potential and are the result of the work of data engineers. The development opportunities in this area are diverse: whether in specialized technical roles, data science or project management. In addition, continuous professional development and certifications open up numerous opportunities for professional development. "At the beginning of this year, for example, I received my Microsoft certification as an Azure Data Engineer and continue to work on my skillset," says Sanja Klein. This keeps her well equipped for the challenges and opportunities of the future.
 

A look at the Asset Intelligence Center AIC system: this is where data for various projects is analyzed, processed and made available.