Cloud-native data lake with streaming ingestion, batch ETL, query engine, and BI dashboards. Handles petabyte-scale analytics.
Difficulty: advanced
Tags: data-engineering, analytics, etl, datalake, gcp
A modern data lake architecture on GCP separates storage from compute using Cloud Storage and BigQuery. This design uses a medallion architecture (raw → curated → aggregated) with Dataflow for streaming and batch ETL, BigQuery for serverless SQL analytics, and Pub/Sub for real-time event ingestion. Built for data engineering teams centralizing analytics from multiple sources into a governed, query-ready data platform.