Data Engineer: What does he do ?

Big Data technologies are booming and so are the jobs related to it. Data Engineers, Scientists, Architects, Analysts and all the others are the “most wanted” positions. Companies need a strong IT structure to store their data and that is when the Data Engineer comes out. But what does he do exactly ?

Data Engineer missions

As Data professionals, they prepare the Data infrastructure. Their job is similar in some ways to software engineers as they design and build to then integrate data. You can picture it as they are the ones who build huge reservoirs to store data, develop it and test it. After that, their main mission is to manage large-scale processing systems and databases and make sure everything works. In order to do so, their job includes building pipelines, integrating data, data cleaning… A large set of skills is needed.

Data Engineer / Data Scientist differences

Some people still wonder how these two jobs are different, so let us explain it. The main activity of Data Engineers is to prepare pipelines for Data Scientists to work on. As they do, they often happen to work closely with Data Scientists but they have really different tasks. On the other hand, Data Architects and Data Engineers actually share similar missions but this is not the point. To put it simple, Data Engineers are data pipelines plumbers : they build data pipelines and maintain it working ; Data Scientists use the pipelines to give meaning to the data. To conclude, Data Engineers come first and make sure Data Scientists can do their job.

Data Engineer skills

A data engineer may be required to have various technical skills as:

  • Database architectures
  • Hadoop-based technologies (MapReduce, Hive…)
  • Data modeling tools
  • Computer code: Python, C/C++ Java, Perl…
  • SQL technologies, NoSQL technologies
  • Data mining
  • Artificial Intelligence, Machine learning and Deep Learning: It is important they understand the algorithms to work with Data Scientists but they obviously do not need to master it like Data Scientists.
  • UNIX, Linux, Solaris and MS Windows


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