Data Engineers have specific requirements but they are not necessary emphasized on your academic background. On the opposite of Data Scientists where a strong academic background is required, Data Engineer positions are less regarding in terms of diplomas and studies levels.
A bachelor's degree in engineering, applied mathematics, computer science or a related field is usually enough to valorize your profile.
Sometimes, companies ask for a master, but it still remains uncommon.
If you’re coming from an undergraduate degree, you can always look into master’s programs and certifications.
IBM, Google Cloud, Cloudera, Microsoft, and Oracle propose their own engineering certifications.
Therefore, the experience is the best value you can add to your profile. A great mentor will certainly be gold for your career as a Data Engineer.
In fact, raw data is ingested and used to become actionable. You’ll need great hands-on experience because having complex systems to deal with is data engineer daily life.
Data Scientists and Data Engineers work in synergy. Based on the work of its Engineering team member, Data Scientists work onto the analysis.
That’s why experience in a startup is also great to learn how to deal with your own integrated data.
You can use the data you have extracted and you become more conscious of your engineering work.
What are the missions of a Data Engineer?
What are the best programming languages in Data Engineering?
What are the key skills of a Data Engineer?
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