Interview questions
Preparing for a data engineering interview at HCL? This page contains 9 real interview questions sourced from verified HCL interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
HCL data engineering interviews typically focus on System Design/Architecture, General/Other, and Python/Coding. The interview bar skews toward harder problems (4 hard vs. 3 easy), suggesting emphasis on depth and system-level thinking.
Use the difficulty filters above to focus your preparation. For each question, attempt your own answer first, then compare with our expert solution. You can also practice these questions in our AI Mock Interview Coach for real-time feedback.
What architecture are you following in your current project, and why?
What is the difference between partitioning and bucketing in Spark, and when would you use bucketing?
What is your cluster configuration?
What is your data volume?
How do you sort a dictionary based on values?
What is the difference between list1 = list2 and list1.copy()?
Explain MapReduce Architecture.
Write PySpark code to extract data from a CSV and create a table.
How do you handle production deployment?
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