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Book synopsis

Master Data Engineering Interviews-from SQL and Python to Spark, Cloud, System Design, and Real-World Production Scenarios.

Modern data engineering interviews go far beyond definitions. Candidates are expected to write SQL and Python, understand distributed systems, troubleshoot production pipelines, evaluate architectural trade-offs, and design scalable data platforms.

Data Engineering Interview: Technical Questions, System Design, SQL, Python, Spark, Cloud, and Real-World Interview Scenarios provides a practical, comprehensive guide for preparing for modern data engineering roles-from foundational concepts to senior-level architecture discussions.

Inside this book, you will learn how to:

• Master data engineering fundamentals, ETL/ELT, CDC, pipelines, and data modeling

• Solve SQL interview problems involving joins, CTEs, window functions, deduplication, ranking, and query optimization

• Prepare for Python and PySpark coding interviews

• Understand Apache Spark architecture, shuffles, partitions, joins, caching, and performance optimization

• Prepare for Apache Kafka, streaming, and real-time data engineering questions

• Work with data warehouses, data lakes, and lakehouses

• Understand Airflow, dbt, Databricks, Snowflake, Redshift, BigQuery, Delta Lake, Iceberg, and Hudi

• Prepare for AWS, Azure, and Google Cloud data engineering interviews

• Design scalable batch, streaming, CDC, analytics, and lakehouse platforms

• Troubleshoot Spark failures, Kafka lag, schema changes, duplicate data, missed SLAs, and pipeline performance problems

• Address data quality, observability, reliability, security, governance, and compliance

• Prepare for senior-level architecture, scalability, technology-selection, cost-optimization, and leadership questions

A major focus of the book is Data Engineering System Design. You will work through realistic case studies involving e-commerce, clickstream analytics, financial transactions, IoT, log analytics, recommendation pipelines, Customer 360, CDC, petabyte-scale data lakes, and real-time analytics.

The book also includes production interview scenarios and rapid-fire questions to help you practice explaining technical decisions clearly and confidently.

Bonus Appendices Include:

• SQL Interview Cheat Sheet
• Python Interview Cheat Sheet
• Spark and PySpark Cheat Sheet
• Data Engineering System Design Checklist
• Cloud Data Engineering Service Mapping
• 100 Essential Data Engineering Interview Questions

Whether you are preparing for your first data engineering role or a senior-level interview, this book helps you develop the technical knowledge, system-design skills, and production problem-solving mindset expected in modern data engineering interviews.

Build the knowledge. Practice the scenarios. Understand the trade-offs. Walk into your next data engineering interview prepared.

Book details

• Full title: Data Engineering Interview
• Subtitle: Technical Questions, System Design, SQL, Python, Spark, Cloud, and Real-World Interview Scenarios
• Author: SK Singh
• Language: English
• Binding: Paperback
• Number of pages: 562
• EAN: 9798174166806
• ID: 53885798
• Publisher: Independently published
• Weight: 1287 g
• Dimensions: 280 × 216 × 29 mm
• Date of publishing: 14. September 2026

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