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      42matters

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      Data Engineer Interview

      2 Oct 2023
      Anonymous interview candidate
      No offer
      Negative experience
      Easy interview

      Application

      I applied online. The process took 4 weeks. I interviewed at 42matters

      Interview

      They wanted to lowball me from the get-go, while they already offer lower 25th percentile salaries. The CTO cannot read a CV correctly, mentions job hopping when it is not there. He then went on a rant about "them training people for two years and them leaving afterwards". Avoid.

      Interview questions [1]

      Question 1

      Describe how you would design a framework.
      Answer question
      1

      Other Data Engineer interview reviews for 42matters

      Data Engineer Interview

      2 Oct 2023
      Anonymous interview candidate
      Zürich
      No offer
      Negative experience
      Average interview

      Application

      I applied online. The process took 4 weeks. I interviewed at 42matters (Zürich) in Sept 2023

      Interview

      First, you will receive a list of questions that need to be filled out and returned back via email (what is your area of improvement, what are the technologies that Data Engineers need to know, etc.). Then it was with the CEO and lasted for half an hour about some general topics/questions (where do you see yourself in five years, etc). After that, you will receive a Data Engineering task to complete for a week (about data cleaning and a concept for a web crawler). They notified me with a generative email that I didn't pass to the next round without any detailed feedback on the task itself. I believe that they are just using applicants to do some tasks for them for free so avoid this company if possible.

      Interview questions [1]

      Question 1

      Can you describe three significant challenges you've faced as a Data Engineer and how you addressed them? How do you envision a typical working week in the role of a Data Engineer? What are your top 3 tools or technologies (not limited to AWS) essential for a Data Engineer? Please explain your choices. We're particularly interested in understanding how candidates approach problems. Imagine you've been given a large dataset that has missing values across multiple columns. How would you address this challenge, and what tools or methodologies would you employ? What would you consider as your biggest strength and area of improvement?
      Answer question
      2

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