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
Data Engineer
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Technical
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hard
Explain how Spark handles data skewness. How would you fix a skewed join when processing Opportunity data where one Account has 90% of the records?
#Spark
#Performance Tuning
#Distributed Computing
Data Engineer
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Technical
•
medium
What is the difference between a Broadcast Hash Join and a Sort-Merge Join in Spark? When would you use each?
#Spark
#Joins
#Optimization
Data Engineer
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Technical
•
medium
How do you handle late-arriving data in a streaming pipeline, such as moving data from Kafka to Spark Structured Streaming?
#Streaming
#Watermarking
#Kafka
Data Engineer
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Technical
•
medium
You have an Airflow DAG that processes 10TB of log data daily, and it is taking too long to complete. How do you troubleshoot and optimize it?
#Airflow
#Optimization
#Bottlenecks
Data Engineer
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Technical
•
medium
How do you ensure data quality and handle bad or corrupted records in a PySpark ETL job?
#PySpark
#Data Quality
#Error Handling
Data Engineer
•
Technical
•
medium
Explain how Kafka consumer groups work. What happens when you add a new consumer to a group?
#Kafka
#Distributed Messaging
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
SimulateUnwritten Rules
Think Out Loud
Always explain your thought process before writing code or drawing architecture.