With evidence
Data engineering
Pipelines, lake, warehouse. 2021 base: Sparkify training, not a client.
Simple explanation
Data arrives dirty, late, duplicated. Engineering is making it usable without lying about its origin.
Technical explanation
Ingest, schema, partitioning, quality checks, warehouse. Spark / S3 / Redshift in the Udacity Sparkify track.
Evidence
Training repos: Data-Lake-Project, Data-Warehouse-Project. Not client work. The current Lab stands on this base; it does not sell it as a professional engagement.