Data Engineering with Python: Build ETL Pipelines and Data Workflows from Scratch

Turn Raw Data into Reliable Insights-One Pipeline at a Time.In a world where data is the new oil, being able to move, clean, transform, and store data efficiently is a game-changing skill. Data Engineering with Python gives you the tools and know-how to build end-to-end ETL pipelines and robust data workflows-from scratch.This book is built for developers, analysts, and aspiring data engineers who want a clear, hands-on guide to real-world data engineering. You'll master how to extract data from APIs and databases, clean and structure it using Python, and load it into data warehouses for downstream analysis. With step-by-step walkthroughs, best practices, and scalable architecture patterns, you'll go beyond the theory and start building production-grade systems.Whether you're working with batch or streaming data, local files or cloud services-this book will equip you with the Python-first approach to build pipelines that are scalable, maintainable, and ready for the modern data stack.✅ What You'll Learn: ETL fundamentals and how to build pipelines from zeroUsing Pandas, SQLAlchemy, and Airflow for real-world workflowsConnecting to APIs, CSVs, SQL, NoSQL, and cloud storageData validation, logging, and error handling for clean pipelinesIntroduction to orchestration, scheduling, and automationBest practices for modular, testable pipeline codePerfect For: Aspiring data engineers and developersData analysts looking to automate and scale workflowsBackend engineers working with data-heavy applicationsAnyone transitioning into data engineering roles

Author:

Miguel Farmer

Publisher:

Independently Published

Publication Date:

Jul 22, 2025

Number of pages:

272 pages

Binding:

Paperback or Softback

ISBN-13:

9798293649228