Round 1: Technical questions - Common data structures and algorithms (search in sorted list, search in linked list, red-black-tree) - How would you implement a priority queue? - HashMap collision resolution strategies - Examples of probabilistic data structures, advantages - Difference between functional and imperative programming. - How would you represent a graph in-memory? - Difference between columnar and row based database. - Difference between inner and outer join. - Explain MapReduce.
Round 2: Coding - Calculate the median of a window of values over an infinity data stream - And a second data question I don't remember
Code some well known algorithm and reason about it. Implement unit tests. Besides many trival questions
difference between datalake, datawarehouse, and what is a lakehouse ?
Ask your knowledge of how Spark works. Also ask if you are familiar with cloud technology. Some other stuff like dataware house and Airflow. The question is confusing sometime though, as the interviewer sometimes cannot tell different concepts apart.
d you have any other offer in hand?
The first question was how to tmplement LinkedList. The second question was to identify if person A knows person B directly or indirectly given a group on LinkedList containing their "know" relation.
Take-Home was answering questions using spark. Nothing too complex. An important element is writing test cases to show a complete example. The panel was more around getting a sense of your technical experience and how you would handle specific cases. There was a live coding session, but nothing was out of the ordinary.
We discussed my data engineering experience and interest in the public sector.
Situational based questions around Data processing in batch and Streaming
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