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Modern Data Engineering: Design, Build, and Scale Reliable Data Systems for Analytics, AI, and the Cloud
Paperback
Series: Data Engineering Domain for Professional, Book 8
Publisher: Independently Published
Published: Feb 8 2026
Pages: 540
Weight: 2.19
Height: 1.40 Width: 6.00 Depth: 9.00
Language: English
Modern Data Engineering is a practical, industry-driven guide that teaches you how real data platforms are designed, built, tested, scaled, and operated in production.
This book goes far beyond basic ETL and tools. It focuses on system thinking, reliability, architecture, cost control, AI readiness, and long-term career growth-the skills that separate average data engineers from senior and principal engineers.
Inside this book, you will learn:
How modern data engineering differs from traditional ETL
How to design batch, streaming, and hybrid data platforms
How to handle real-world failures, data quality issues, and outages
How to build AI-ready and ML-friendly data systems
How to test, deploy, and operate data pipelines safely
How data teams scale, organize, and succeed in real companies
How to prepare for interviews and grow a long-term data engineering career
This book is written in clear, practical language with real-world scenarios, case studies, and engineering trade-offs-not academic theory.
Whether you are:
A student or fresher entering data engineering
A working data engineer aiming for senior roles
An analytics or software engineer transitioning into data engineering
A professional preparing for product-based or global tech interviews
This book will help you think like a real data engineer, not just use tools.
If you want to build data systems that last-and a career that grows with them-this book is for y
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