Capgemini

Global leader in partnering with companies to transform and manage their business by harnessing the power of technology.

4 Rounds ~21 Days Medium

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The Interview Loop

Recruiter Screen (30 min)

Standard fit check, behavioral questions, and resume overview.

Technical Loop (3-4 Rounds)

Deep dive into domain knowledge, coding, and system design.

Interview Question Bank

All Roles Data Engineer 10

All Topics Big Data 10 SQL 5 Cloud 4 Culture Fit 3 System Design 3 Python 3 Data Modeling 2 Leadership 2

Data Engineer • Coding • medium

Write a PySpark script to read a CSV file, drop rows with nulls in a specific column, and write the output to Parquet partitioned by a date column.

#PySpark #DataFrames #I/O Operations

Practice

Data Engineer • Coding • hard

Write PySpark code to flatten a deeply nested JSON schema into a flat tabular DataFrame.

#PySpark #Complex Data Types #JSON

Practice

Data Engineer • Coding • medium

Given a PySpark DataFrame, how do you find the second most frequent item in a specific column?

#PySpark #Aggregations #Window Functions

Practice

Data Engineer • Technical • hard

How does Apache Spark handle data skewness? Explain techniques like salting.

#PySpark #Performance Optimization #Data Skew

Practice

Data Engineer • Technical • easy

What is the difference between narrow and wide transformations in Spark? Give examples of each.

#PySpark #Spark Architecture #Transformations

Practice

Data Engineer • Technical • medium

Explain Broadcast Hash Join and Sort Merge Join in Spark. When would you use one over the other?

#PySpark #Joins #Optimization

Practice

Data Engineer • Technical • medium

How do you manage memory in PySpark? Explain the difference between cache() and persist().

#PySpark #Memory Management

Practice

Data Engineer • Technical • hard

Explain the Catalyst Optimizer in Spark. What are its main phases?

#Spark Architecture #Catalyst Optimizer

Practice

Data Engineer • Technical • medium

How do you handle the 'small files problem' in Spark and HDFS/Cloud Storage?

#PySpark #Storage Optimization

Practice

Data Engineer • Technical • easy

What is the difference between repartition() and coalesce() in PySpark?

#PySpark #Partitioning

Practice

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Senior Engineer

Focuses on core competencies, system constraints, and clear communication.

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Think Out Loud

Always explain your thought process before writing code or drawing architecture.

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