Data Engineering Essentials

Data is the foundation of modern business.

Every dashboard, recommendation engine, AI model, analytics report, and business decision depends on one thing: reliable data.

But raw data is rarely useful on its own.

The truth is simple:

Organizations need engineers who can collect, move, transform, validate, store, and deliver data at scale.

That is the role of the modern Data Engineer.

In Data Engineering Essentials, Ethan Vale provides a practical guide to designing and building modern data platforms using the tools, architectures, and best practices used by today's leading technology companies.

Written for aspiring data engineers, software developers, analysts, cloud professionals, DevOps engineers, and technology leaders, this book explains the complete modern data stack-from foundational SQL and Python skills to large-scale processing, cloud data warehouses, streaming platforms, and MLOps.

Inside this book, you'll learn:

• SQL for modern data engineering
• Python for data pipelines and automation
• Data modelling and warehouse design
• ETL and ELT architecture
• Apache Airflow orchestration
• Apache Kafka streaming systems
• Data quality and governance
• Snowflake, BigQuery, and Redshift
• Data lakes and lakehouse architecture
• Apache Spark processing at scale
• dbt transformation frameworks
• DataOps and pipeline automation
• Cloud-native data platforms
• Real-time analytics and streaming architectures
• MLOps and AI data infrastructure
• Building scalable modern data ecosystems