Serverless Data Engineering: Designing Scalable Pipelines Without Managing Infrastructure is a practical and forward-looking guide to building modern, event-driven data systems in the cloud--without the complexity of managing servers. As organizations shift toward agile, cost-efficient architectures, serverless technologies are reshaping how data is processed, stored, and delivered. This book walks you through the core principles of serverless computing and how they apply to data engineering--from ingestion and transformation to orchestration and automation. Learn how to leverage cloud-native services like AWS Lambda, Google Cloud Functions, Azure Data Factory, and managed streaming platforms like Kinesis and Pub/Sub to build efficient, resilient, and scalable data pipelines. Through real-world examples, architectural patterns, and hands-on tutorials, you'll discover how serverless enables rapid development, automatic scaling, and pay-per-use efficiency--all while reducing operational overhead. Whether you're modernizing legacy systems or designing greenfield data solutions, this book provides the tools and strategies you need to engineer data workflows that are cloud-smart and future-ready.
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