Sr Data Engineer Interview Questions

2,566 sr data engineer interview questions shared by candidates

A. Core Data Engineering Concepts SQL (joins, window functions, performance tuning) Data Modeling (star vs snowflake, normalization) ETL/ELT pipelines (batch vs streaming, orchestration tools like Airflow) B. Apache Spark / PySpark Catalyst Optimizer & Tungsten Narrow vs Wide transformations Joins (broadcast, sort-merge), Skew handling AQE (Adaptive Query Execution) Partitioning, Predicate Pushdown Execution Plan (DAG → Stage → Tasks) Spark UI and Job Debugging SCD Type 2 Implementation in PySpark C. AWS S3, Glue, Athena, Lambda, EMR, Redshift Event-driven design (S3 → EventBridge → Lambda) Security: IAM roles, bucket policies, encryption CI/CD in AWS (CodePipeline, CloudFormation) D. Python Writing modular, reusable code Working with Pandas, Boto3 (for AWS interaction) Exception handling, logging Lambda functions and decorators E. Kafka / Streaming Kafka topic partitioning, consumer groups Offset management Integration with Spark Structured Streaming
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Senior Data Engineer

Interviewed at EPAM Systems

4
Jul 21, 2025

A. Core Data Engineering Concepts SQL (joins, window functions, performance tuning) Data Modeling (star vs snowflake, normalization) ETL/ELT pipelines (batch vs streaming, orchestration tools like Airflow) B. Apache Spark / PySpark Catalyst Optimizer & Tungsten Narrow vs Wide transformations Joins (broadcast, sort-merge), Skew handling AQE (Adaptive Query Execution) Partitioning, Predicate Pushdown Execution Plan (DAG → Stage → Tasks) Spark UI and Job Debugging SCD Type 2 Implementation in PySpark C. AWS S3, Glue, Athena, Lambda, EMR, Redshift Event-driven design (S3 → EventBridge → Lambda) Security: IAM roles, bucket policies, encryption CI/CD in AWS (CodePipeline, CloudFormation) D. Python Writing modular, reusable code Working with Pandas, Boto3 (for AWS interaction) Exception handling, logging Lambda functions and decorators E. Kafka / Streaming Kafka topic partitioning, consumer groups Offset management Integration with Spark Structured Streaming

L1: core technical discussion for 1 hour( coding, system design, scenario based) L2: Client interviews ( 2 hours, detailed discussion about system design and integration and analytics, KPI) L3: Client interviews ( 2 hours, live project implementation)
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Senior Data Engineer

Interviewed at Persistent Systems

4.2
Oct 23, 2025

L1: core technical discussion for 1 hour( coding, system design, scenario based) L2: Client interviews ( 2 hours, detailed discussion about system design and integration and analytics, KPI) L3: Client interviews ( 2 hours, live project implementation)

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