{ "item_title" : "Pipeline Engineer", "item_author" : [" Richard Boozman "], "item_description" : "Design scalable, reliable, and production-ready data platforms for modern analytics and machine learningData systems are the backbone of modern organizations.From analytics dashboards and business intelligence to machine learning pipelines and real-time decision systems, companies depend on reliable data infrastructure to operate effectively.Pipeline Engineer is a practical, engineering-focused guide to building modern data platforms using Python, Apache Airflow, dbt, and cloud-native infrastructure.This book teaches developers and data engineers how to design, orchestrate, transform, monitor, and scale production-grade data systems.Why modern data engineering mattersOrganizations today face challenges such as: fragmented data sourcesunreliable pipelines and failed jobspoor data quality and governancescaling transformation workloadsoperational complexity across cloud systemsmaintaining observability and lineageBuilding dependable data infrastructure requires both software engineering discipline and operational reliability.What you will learnfundamentals of modern data architecturedesigning ETL and ELT workflowsworkflow orchestration with Airflowtransformation modeling with dbtscalable data ingestion patternsdata warehouse and lakehouse conceptspipeline testing and validationobservability and monitoring strategiescloud-native deployment workflowssecurity, governance, and access managementFrom raw data to reliable platformsThroughout the book, you will learn how to: design maintainable data pipelinesorchestrate complex workflow dependenciesbuild reusable transformation layersimprove data quality and reliabilitymonitor pipelines proactivelyscale data infrastructure across cloud environmentsmanage production operations confidentlyEach chapter focuses on practical workflows used in real-world data engineering teams.Practical applicationsanalytics engineering platformsbusiness intelligence pipelinesmachine learning data infrastructureevent-driven data systemscloud-native ETL and ELT platformsenterprise reporting and governance systemsThese examples reflect real production data engineering challenges.Who this book is fordata engineersanalytics engineersbackend developerscloud engineersmachine learning infrastructure teamssoftware engineers transitioning into data platformsIf you want to build scalable, maintainable, and production-ready data systems, this book provides the roadmap.Move data reliably.Transform intelligently.Engineer infrastructure that scales.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/818/030/9798180305015_b.jpg", "price_data" : { "retail_price" : "24.99", "online_price" : "24.99", "our_price" : "24.99", "club_price" : "24.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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