Cloud & Tools questions from Incedo data engineering interviews.
These cloud & tools questions are sourced from Incedo data engineering interviews. Each includes an expert-level answer. This set leans toward senior-level depth (3 of 7 are tagged hard). Recurring themes are spark, python, and etl — these patterns appear most often in real interviews and reward the deepest preparation. Many of these questions also surface at EY and Tech Mahindra, 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 7 curated questions: 3 easy, 1 medium, and 3 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 (3), python (1), etl (1), bigquery (1), join (1), and optimization (1). 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.
Explain the difference between Azure Data Factory (ADF) and Databricks.
What are the key components of AWS Glue, and how do they work together?
What is Azure Data Factory (ADF), and what are its main components?
What is Snowflake's architecture, and why is it unique?
What is the difference between S3 and HDFS?
What is the role of AWS Lambda in a data engineering pipeline?
What is the role of the Integration Runtime (IR) in ADF?
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