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      Flow Traders

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      Senior Platform Data Engineer Interview

      1 Nov 2022
      Anonymous interview candidate
      Amsterdam
      No offer
      Negative experience
      Difficult interview

      Application

      I applied online. The process took 3 weeks. I interviewed at Flow Traders (Amsterdam) in Oct 2022

      Interview

      I applied online on the Flow Traders website. 1- Call from the recruiter 2- Take home assignment consists of two parts: a - System design: design a system get data from trading systems and make it available for historical analysis, the trading systems provide data with two ways, gRPC and a dump file every minute. b - PySpark code, giving this input write a code to generate the output, join two dataframes 3- Technical interview to discuss the assignment: mainly focused on my CV and previous experience and a little bit about the system design solution the team lead which was supposed to be in this interview was on vacation. 4- round 2 technical interview: with the team lead and a data engineer, more focused on software engineer and how programming language works as they need a very strong data engineer with extended knowledge and experience in data engineering and platform engineering, All but last part was OK, I got a rejection few days later

      Interview questions [9]

      Question 1

      How does python store data in memory?
      Answer question

      Question 2

      How does multithreading works in python? when you submit a function to the pool does it starts a thread for each function?
      Answer question

      Question 3

      How does the programming language handle the allocated memory that doesn't have a reference? how does that work?
      Answer question

      Question 4

      How does the windowing works in spark?
      Answer question

      Question 5

      what type of join do you use to join a big dataset with a small dataset in spark?
      Answer question

      Question 6

      How do we increase the topic parallelism in kafka?
      Answer question

      Question 7

      How to handle scaling up and down in Kafka? how to handle decreasing the number of partitions in each topic?
      Answer question

      Question 8

      How did you deploy the spark operator on Kubernetes in your previous job?
      Answer question

      Question 9

      How do you prevent duplications/overwriting final data in Lambda architecture in case the streaming path was down for a while and then got fixed?
      Answer question
      12