The differences, including responsibilities, tools, languages, job outlook, salary, between data engineers and data scientists are explained next. The data focus is now more on retrieving valuable insights from data. The importance of data management has slowly started to sink in the industry.
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Responsibilities
The data engineer is someone who develops, constructs, tests and maintains architectures, such as databases and large-scale processing systems. |
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Data engineers deal with raw data that contains human, machine, or instrument errors. They will need to recommend and sometimes implement ways to improve data reliability, efficiency, and quality. To do so, they will need to employ a variety of languages and tools to marry systems together, so the information can be further processed by data scientists.
| Very closely related to these two is the fact that data engineers will need to ensure that the architecture that is in place supports the requirements of the data scientists and the business. Lastly, to deliver the data to the data science team, the data engineering team will need to develop data set processes for data modeling, mining, and production. |
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Math teacher: If I have three bottles in one hand and two in the other hand, what do I have? Student: A drinking problem. |