GCP · Customer Data Platform
CDP re-architected on GCP — 300B+ events processed with privacy-first design.
We re-architected a CDP on GCP with BigQuery-native ingestion, privacy vault and consent-aware activation — scaling to 300B+ events/month.
[Events / mo]
300B+
[Query speed]
+2.4×
[Consent leaks]
0
[ The Problem ]
Where the business was stuck.
Customer Data Platform couldn't process billions of events monthly while meeting privacy and consent requirements.
[ Key Challenges ]
- ▸Streaming ingestion pipeline hitting scale ceiling
- ▸Consent enforcement bolted on rather than built-in
- ▸Query performance degrading as data grew
Our approach
How we engineered
the outcome.
STEP 01
Pub/Sub + Dataflow for ingestion, BigQuery for warehouse
STEP 02
Privacy vault with per-user consent scope enforcement at query time
STEP 03
Materialized views + BI Engine for interactive query speed
[ Solution highlights ]
Delivered — measured — in production.
- ✓300B+ events processed per month
- ✓Consent enforcement in SQL layer — provable to auditors
- ✓Query performance 2.4× faster on the same footprint
[ Tech stack ]
Built on GCP.
GCP BigQuery
Pub/Sub
Dataflow
Terraform
"
Scale and privacy stopped being a trade-off — the architecture enforces both.