Data Pipeline Engineering with Azure Databricks

Organizations rely on clean, timely data to make critical decisions, but building and maintaining reliable pipelines can be complex. This text-based course guides you through the entire lifecycle of data engineering on Azure Databricks, helping you transition from basic queries to orchestrating robust, automated workloads. You will start by learning key terminology, basic workspace concepts, and foundational architecture before moving into practical pipeline design.\n\nWhat you'll learn:\n- Understand core Azure Databricks architecture and workspace fundamentals\n- Build scalable data ingestion and transformation pipelines using Delta Lake\n- Orchestrate and schedule complex workloads using Databricks Jobs\n- Implement version control and basic deployment workflows for your notebooks\n- Monitor pipeline performance and set up alerts for automated workloads\n- Apply modern observability practices to troubleshoot and optimize data processing\n\nThrough clear written explanations and practical code examples, you will explore how to configure workspaces, write transformation logic, and automate production pipelines. This course is designed for beginners to data engineering and cloud data platforms, with no prior Databricks experience required. Start reading today to master the fundamentals of modern data pipeline orchestration.