Interview questions
Preparing for a data engineering interview at Globant? This page contains 13 real interview questions sourced from verified Globant interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Globant data engineering interviews typically focus on Spark/Big Data, SQL, and Behavioral. The interview bar skews toward harder problems (7 hard vs. 4 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.
Tell me about yourself and your experience.
Explain the concept of checkpointing in Spark and why it is important.
How do you drop columns with null values in PySpark?
Explain Dynamic Partition Pruning error and how to fix it.
How do you convert 3 rows into one column in SQL?
How do you count occurrences in a column in SQL?
How do you keep a specific column on top in SQL?
Explain read and write modes in Spark.
How do you convert an array column to multiple columns in PySpark?
How does Adaptive Query Execution (AQE) work?
What is a serializer in Spark?
What is the difference between MapReduce and Spark?
What is the difference between head() and take() in PySpark?
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