Interview questions
Preparing for a data engineering interview at Coforge? This page contains 15 real interview questions sourced from verified Coforge interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Coforge data engineering interviews typically focus on Spark/Big Data, System Design/Architecture, and Python/Coding. The interview bar skews toward harder problems (7 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 are traits in Scala, and how are they different from classes?
What is the difference between cache() and persist() in Spark? When would you use each?
What is the difference between groupByKey and reduceByKey in Spark?
What is the difference between narrow and wide transformations in Apache Spark? Explain with examples.
What is the difference between partitioning and bucketing in Spark, and when would you use bucketing?
Can you explain the architecture of Apache Spark and its components?
When would you architecturally choose Dataset[T] over DataFrame in a Scala Spark pipeline, and what are the scalability and portability trade-offs? Include type-safety benefits vs. operational constraints.
How are strings handled in Scala? How are they different from Java strings?
Explain the DAG in Spark and how it plays a role in execution.
How do you handle very large datasets in Spark to ensure scalability and efficiency?
How many stages are created in a Spark job, and how are they formed?
How would you handle unstructured data in Hive?
Explain how Spark handles fault tolerance. How does it recover from node failures?
How do you ensure data quality in a big data pipeline, and what strategies do you use for data validation?
How does Spark handle distributed computing, and what challenges have you faced while working on distributed systems?
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