Interview questions
Preparing for a data engineering interview at Capco? This page contains 22 real interview questions sourced from verified Capco interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Capco data engineering interviews typically focus on Spark/Big Data, SQL, and Cloud/Tools. The interview bar skews toward harder problems (10 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 is the difference between groupByKey and reduceByKey in Spark?
Demonstrate the difference between DENSE_RANK() and RANK()
Write a Python function to check if a string is a palindrome.
Implement a Spark job to find the top 10 most frequent words in a large text file.
How would you monitor a data pipeline in AWS to ensure SLA compliance?
How would you pass data between Lambda functions in Step Functions?
How would you use Amazon Glue to merge small files?
What alternatives to Kinesis would you consider for real-time data ingestion?
What are the differences between SSE-S3, SSE-KMS, and SSE-C encryption?
How would you implement custom alarms for data delays or job failures?
What is the impact of multipart uploads on lifecycle policies?
Compare Glue partition discovery with Hive MSCK/ADD PARTITION. Explain the operational and cost implications of crawler-based vs. partition-projection approaches. When does partition projection become necessary, and what are its limitations?
How would you handle data type changes for an existing column?
How would you prevent small file problems in S3 when loading data into Redshift?
What strategies would you use to manage dynamic partitions efficiently?
Explain how Glue's Spark-based architecture handles data parallelism.
How does Glue Catalog handle schema versioning compared to Hive Metastore?
How would you manage transitions to Glacier Instant Retrieval and Deep Archive?
How would you migrate metadata from Hive Metastore to Glue?
Describe handling schema evolution in AWS Redshift without downtime.
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