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{ "item_title" : "Advanced Python Patterns for Data Engineering", "item_author" : [" Abhishek Kumar "], "item_description" : "Are you still writing one-off scripts instead of building real data pipelines?Most Python developers struggle to transition into data engineering because they lack one thing - production-level design skills.This book changes that.Advanced Python Patterns for Data Engineering is a practical, real-world guide to building scalable, reliable, and production-ready data systems using Python.Instead of focusing on theory, this book teaches you how real data engineers design pipelines that run daily, handle failures, and scale to millions of records. What You'll LearnHow to design reusable ETL and ELT pipelinesAdvanced Python patterns for scalable data workflowsIncremental loading, idempotency, and schema evolutionError handling, retry strategies, and circuit breakersData validation, monitoring, and observabilityParallel and distributed processing conceptsPartitioning, caching, and performance optimizationBatch vs streaming architectureHow to build production-ready pipelines from scratch Real-World FocusThis book includes: real production case studiesarchitecture-level thinkingcomplete end-to-end projectindustry best practices Who This Book Is ForPython developers moving into data engineeringaspiring data engineersdata analysts upgrading to pipeline developmentengineers preparing for interviewsprofessionals who want to build production systems What Makes This Book DifferentUnlike most books, this is not about writing scripts.It's about: designing systems handling real-world failures building scalable data platforms", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/825/266/9798252666761_b.jpg", "price_data" : { "retail_price" : "49.99", "online_price" : "49.99", "our_price" : "49.99", "club_price" : "49.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Advanced Python Patterns for Data Engineering|Abhishek Kumar

Advanced Python Patterns for Data Engineering : Build Production-Ready ETL Pipelines, Scalable Data Systems, and Reliable Data Platforms

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Overview

Are you still writing one-off scripts instead of building real data pipelines?

Most Python developers struggle to transition into data engineering because they lack one thing - production-level design skills.

This book changes that.

Advanced Python Patterns for Data Engineering is a practical, real-world guide to building scalable, reliable, and production-ready data systems using Python.

Instead of focusing on theory, this book teaches you how real data engineers design pipelines that run daily, handle failures, and scale to millions of records.


What You'll Learn
  • How to design reusable ETL and ELT pipelines

  • Advanced Python patterns for scalable data workflows

  • Incremental loading, idempotency, and schema evolution

  • Error handling, retry strategies, and circuit breakers

  • Data validation, monitoring, and observability

  • Parallel and distributed processing concepts

  • Partitioning, caching, and performance optimization

  • Batch vs streaming architecture

  • How to build production-ready pipelines from scratch


Real-World Focus

This book includes:

  • real production case studies

  • architecture-level thinking

  • complete end-to-end project

  • industry best practices


Who This Book Is For
  • Python developers moving into data engineering

  • aspiring data engineers

  • data analysts upgrading to pipeline development

  • engineers preparing for interviews

  • professionals who want to build production systems


What Makes This Book Different

Unlike most books, this is not about writing scripts.

It's about:
designing systems
handling real-world failures
building scalable data platforms

This item is Non-Returnable

Details

  • ISBN-13: 9798252666761
  • ISBN-10: 9798252666761
  • Publisher: Independently Published
  • Publish Date: March 2026
  • Dimensions: 9 x 6 x 0.33 inches
  • Shipping Weight: 0.48 pounds
  • Page Count: 156

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