Modern Data Engineering

Build Reliable Pipelines, Warehouses, and Analytics Systems for Real-World Data Workflows

Owen Fletcher

• Publisher: Chiify
• Year: 2026
• Topic: Computer Science
• eBook ISBN:
  9798259608139
• Subtopic: Databases
• Index: Computer Science

**Master the foundations of modern data engineering and learn how to build reliable, scalable data systems from the ground up.** Data is one of the most valuable assets in today's organizations—but raw data alone has little value. It must be collected, organized, transformed, tested, and delivered before it can power analytics, business intelligence, dashboards, and artificial intelligence. That is where modern data engineering comes in. **Modern Data Engineering** provides a practical, beginner-friendly guide to the principles, architectures, and workflows used to build dependable data platforms. Rather than focusing on a single vendor or tool, this book teaches the core concepts that remain valuable across today's rapidly evolving data ecosystem. Inside, you'll learn how to: * Understand the role of a modern data engineer * Design reliable data pipelines from source to analytics * Work with databases, data warehouses, data lakes, and lakehouses * Build efficient ETL and ELT workflows * Ingest data from APIs, databases, files, and SaaS platforms * Store and organize data using modern file formats and partitioning strategies * Transform raw data into analytics-ready datasets using SQL * Design fact tables, dimension tables, and star schemas * Orchestrate automated workflows and pipeline scheduling * Understand batch and real-time data processing * Improve data quality through testing and validation * Implement governance, metadata management, security, and access control * Build scalable cloud-based data engineering solutions * Complete an end-to-end data engineering project suitable for your professional portfolio Whether you're an aspiring data engineer, software developer, data analyst, cloud professional, or IT student looking to expand your technical skills, this book offers a structured learning path that combines essential theory with practical design principles. By the end of the book, you'll understand how modern data platforms are built, how data flows through an organization, and how to design scalable, trustworthy data systems that support informed decision-making and future-ready applications. If you're ready to build the skills behind today's data-driven organizations, **Modern Data Engineering** is your practical guide to getting started.

Table of contents

• Modern Data Engineering
• Modern Data Engineering
• Build Reliable Pipelines, Warehouses, and Analytics Systems for Real-World Data Workflows
• Chapter 1: What Data Engineering Is
• Chapter 2: The Modern Data Engineering Ecosystem
• Chapter 3: Understanding Data Sources
• Chapter 4: Data Ingestion
• Chapter 5: ETL, ELT, and Pipeline Design
• Chapter 6: Data Storage and File Formats
• Chapter 7: Data Warehousing
• Chapter 8: Data Transformation with SQL
• Chapter 9: Data Modeling for Analytics
• Chapter 10: Workflow Orchestration
• Chapter 11: Real-Time Data and Streaming
• Chapter 12: Data Quality and Testing
• Chapter 13: Governance, Security, and Metadata
• Chapter 14: Cloud Data Engineering
• Chapter 15: Building a Complete Data Engineering Project
• Introduction:
• The Role of Modern Data Engineering
• Chapter 1: What Data Engineering Is
• Chapter 2: The Modern Data Engineering Ecosystem
• Chapter 3: Understanding Data Sources
• Chapter 4: Data Ingestion
• Chapter 5: ETL, ELT, and Pipeline Design
• Chapter 6: Data Storage and File Formats
• Chapter 7: Data Warehousing
• Chapter 8: Data Transformation with SQL
• Chapter 9: Data Modeling for Analytics
• Chapter 10: Workflow Orchestration
• Chapter 11: Real-Time Data and Streaming
• Chapter 12: Data Quality and Testing
• Chapter 13: Governance, Security, and Metadata
• Chapter 14: Cloud Data Engineering
• Chapter 15: Building a Complete Data Engineering Project
• About the Author
• About the Book
• Acknowledgement