Data engineering is the discipline of moving, shaping and serving data reliably at scale. This course covers the foundations that outlast any tool: how to model data for its consumers, how to build batch and streaming pipelines that are correct and idempotent, how to choose and operate storage and processing engines, how to orchestrate and test pipelines, how to keep data trustworthy with quality checks and observability, and how to run a data platform as production infrastructure. Every lesson ends with an action step that builds a working project.

For software engineers, analysts and database professionals moving into data engineering roles.

Modules

Foundations

Lessons

• What Data Engineers Build Preview
• Data Modelling Fundamentals
• SQL for Engineers

Batch Pipelines

Lessons

• Ingestion Patterns
• Transformation and Idempotency
• Processing Engines and Scale

Streaming

Lessons

• Streaming Fundamentals
• Stream Processing Patterns
• Choosing Between Batch and Streaming

Storage and Platforms

Lessons

• Warehouses, Lakes and Lakehouses
• File Formats, Partitioning and Performance
• Serving Layers and Consumers

Orchestration Quality and Observability

Lessons

• Orchestration and Dependencies
• Data Quality and Testing
• Data Observability and Lineage

Operating the Platform

Lessons

• Security, Privacy and Governance
• Cost Management
• Reliability, Operations and the Career