Interview questions
Preparing for a data engineering interview at HashedIn? This page contains 10 real interview questions sourced from verified HashedIn interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
HashedIn data engineering interviews typically focus on Spark/Big Data, Python/Coding, and SQL. The interview bar skews toward harder problems (5 hard vs. 2 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 strategies can you use to handle skewed data in Spark?
Write a Python function to check if a string is a palindrome.
How does Spark's Catalyst Optimizer work? Explain its stages.
Walk through the three AQE features in Spark 3.x (coalesce, join switch, skew join)—how they operate at shuffle boundaries, which configs enable them, and what happens when AQE cannot help.
What is Adaptive Query Execution (AQE) in Spark 3.x, and how does it improve performance?
Implement a function to find the maximum sum subarray (Kadane's algorithm).
Implement a function to reverse a string without using built-in methods.
How do you design a scalable and fault-tolerant data warehouse on a cloud platform?
Explain the differences between Spark's shuffle and broadcast join. When would you use each?
Design a Data Warehouse for an e-commerce platform.
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