Real interview questions asked at Hexaware. Practice the most frequently asked questions and land your next role.
Hexaware data engineering interviews test your ability across multiple domains. These questions are sourced from real Hexaware interview experiences and sorted by frequency. Practice the ones that matter most. This set leans toward senior-level depth (6 of 13 are tagged hard). Recurring themes are spark, optimization, and partition — these patterns appear most often in real interviews and reward the deepest preparation. Many of these questions also surface at Altimetrik and American Express, so the preparation transfers across companies. Average answer is around 1 minute of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 13 curated questions: 6 easy, 1 medium, and 6 hard. The balanced mix of difficulties makes this set suitable for engineers at any career stage.
The most frequently tested areas in this set are spark (7), optimization (6), partition (6), python (2), sql (2), and window (2). Focusing on these topics will give you the highest return on your preparation time.
Start with the easy questions to warm up and solidify fundamentals. Medium-difficulty questions form the bulk of real interviews — spend the most time here and practice explaining your reasoning out loud. Hard questions often appear in senior and staff-level rounds; attempt them after you're comfortable with the basics. For each question, try answering before revealing the solution. Use our AI Mock Interview to simulate real interview conditions and get instant feedback on your responses.
What is the difference between SparkSession and SparkContext in Spark?
How do you copy all files from one source path to target in ADF?
Explain Job vs. Interactive Clusters.
How do you increase job performance? What techniques and optimizations?
How do you run one notebook in another notebook?
How do you see files before update (history records/versioning)?
Explain how to implement cumulative sum in SQL.
Discuss Delta Logs file format and its significance.
Explain SCD1 and SCD2 in Databricks PySpark with examples.
Explain aggregation functions in PySpark with examples and use cases.
How do you access Delta Logs?
How do you connect to Blob Storage in Databricks?
What are the steps to connect to Salesforce?
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