Mastering Modern Data Engineering: A Practical Guide to Building Scalable, Reliable Data Pipelines with Spark, Airflow, Kafka, and the Cloud

By Ethan M. Rhodes

Mastering Modern Data Engineering: A Practical Guide to Building Scalable, Reliable Data Pipelines with Spark, Airflow, Kafka, and the Cloud

The Complete Guide to Building High-Performance Data Platforms From Batch to Real-Time, On-Prem to Cloud

Are you ready to go beyond basic ETL scripts and start thinking like a true modern data engineer?

Whether you're a new data professional, an experienced engineer upgrading your cloud skills, or a developer pivoting into the data world, this hands-on guide is your one-stop roadmap to mastering scalable, production-grade data systems.

Mastering Modern Data Engineering cuts through the noise and delivers a clear, practical blueprint for designing resilient data pipelines using the most powerful tools in the industry: Apache Spark, Airflow, Kafka, Delta Lake, and major cloud platforms like AWS, GCP, and Azure.

What You'll Learn Inside:

Batch & Stream Processing at Scale
Learn the difference between real-time and batch architectures-and when to use tools like Spark, Flink, or Kafka.

Building with Apache Spark
Write high-performance batch jobs using RDDs, DataFrames, and SparkSQL. Tackle joins, aggregations, skew, and partitioning like a pro.

Pipeline Orchestration with Airflow
Master DAG design, scheduling strategies, modular pipelines, and production-grade alerting and monitoring setups.

Cloud-Native Data Engineering
Deploy infrastructure using Terraform, containerize your jobs with Docker & Kubernetes, and optimize pipelines for cost and scalability.

End-to-End Case Studies
Walk through real-world projects like e-commerce analytics, real-time user tracking, and building an internal data platform from scratch.

Modern Topics That Matter
Data Mesh, observability, generative AI in pipelines, data contracts, testing, compliance, CI/CD for data-this book covers it all.

Who This Book Is For:

Data Engineers looking to level up to modern tooling and cloud practices

Analytics Engineers and DBAs transitioning into data infrastructure roles

Software Developers exploring the data engineering career path

Engineering leads building or scaling cloud-based data platforms

Bonus Features:

Interview question bank for data engineers

Certification roadmap for AWS, GCP, and Azure

AI prompt cheat sheet for accelerating pipeline development

Trusted by Engineers, Built for Real Work

Whether you're building your first DAG or managing petabyte-scale infrastructure, Mastering Modern Data Engineering will help you confidently architect solutions that scale-today and tomorrow.

Perfect for:
Airflow - Spark - Kafka - Flink - dbt - Snowflake - BigQuery - Dataflow - Delta Lake - Kubernetes - AWS - GCP - Azure - Terraform - Observability - Real-Time Streaming - Data Platform Architecture - Interview Prep

Start building like a senior data engineer.Own your stack. Own your impact.

• Format: Paperback
• Language: English
• ISBN: B0FKFQWCTQ
• ISBN13: 9798294650575
• Release Date: July 2025
• Publisher: Independently Published
• Length: 240 Pages
• Weight: 1.25 lbs.
• Dimensions: 0.5" x 8.5" x 11.0"