Learning path · Intermediate · 9 steps

Data Engineer: Reliable Pipelines from Source to Warehouse

Build pipelines people can trust: extraction and change data capture, idempotent loading, late data and backfills, dimensional modelling, dbt and orchestration, data quality, cost and privacy, plus the messaging and idempotency foundations underneath.

Course ETL and Data Pipelines
The core course: from ETL vs ELT to data quality, cost and privacy
Decision guide Event Sourcing vs CRUD + Audit Log vs CDC
Where change data capture fits
Decision guide At-Most-Once vs At-Least-Once vs Effectively-Once
At-least-once, at-most-once and exactly-once in practice
Decision guide Temporal vs Step Functions vs Queue + State Machine
Choosing an orchestrator or workflow engine
Quiz (sign in) Data Engineering Quiz
Course Idempotency & Retry-Safe Systems
Safe retries and deduplication in depth
Course Queues & Background Processing in Depth
Brokers, ordering, lag and backpressure
Coding practice Data consistency at scale
Practise consistency problems in code
Topic ETL and Data Pipelines
Interview questions, most-asked first

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