Microsoft, Seattle data engineer positions ask for experience on OOP programming on either Python or C++ etc. In my extensive DE exp I have never used linked lists/sorting algos/ big o notation optimization/ design patterns for any client implementations of large or small Data engineering projects. How do you approach interviews for such positions? Or totally skip such roles with unrealistic asks?

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What’s your DE experience in then? I wouldn’t call that unrealistic for certain data engineering roles, but this sounds like DE roles that work closely on software where this kind of knowledge is important. You’re probably just not the right fit for the role as I wouldn’t say these are unrealistic requirements.

The public static void main junkies think by doing CS, psvm can be applied to all scenarios. As I said earlier speculating is just garbage. I haven’t used even half of the C++/ Java/Design Patterns/Algos/ O-notation stuff I learnt, in any of the DE projects. Yeah ‘minor’ class/object/packing but nothing comparable to an enterprise grade OOP programming project. I believe(same as you speculate) DE roles in SWE divisions require 30% of DE and 70% OOP so that if required they could move talent to other non-DE roles.

I build models and prototype pipelines rather than operationalize production code. Still, I've used some OO concepts and regularly need to be aware of the general time complexity of whatever high level data transformations I make, be they through SQL or pandas or Spark. Else my workloads just won't run. From data engineers, a job which is normally all about setting up efficient pipelines unlike mine, I'd expect much more.

Agreed some OOP concepts such as class/object/packing in pyspark is needed but nothing as crazy as app developer level knowledge. Without basic knowledge DE would be more of data analyst. The interviewer at MSFT needed app developer grade knowledge(leetcode and stuff). That time complexity you mentioned is way different from algo complexity/big o notation complexity coz bulk load optimization problem vs single iteration based optimizations are worlds apart.

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