Business Required:

The client operated multiple marketing systems, generating campaign, customer, lead, channel, and engagement datasets from different platforms and external feeds. The existing workflow relied on manual processing, inconsistent validation, and limited monitoring capabilities, resulting in operational delays and unreliable analytics readiness.

The business required a modern ETL platform that could:

• Automate marketing data ingestion

• Improve validation and data quality

• Enable faster analytics readiness

• Reduce manual operational effort

• Improve error traceability

• Support scalable ETL orchestration

• Improve workflow monitoring

• Establish production-ready support operations

Solution Summary

The solution modernized the marketing ETL ecosystem by introducing a cloud-based architecture where:

• Marketing source files were ingested through Cloud Data Fusion

• Wrangler handled validation and cleansing workflows

• BigQuery served as the central analytical warehouse

• Error records were routed into dedicated error tables

• Airflow orchestrated workflow scheduling and monitoring

• BQ Shell supported operational execution workflows

• SRE monitoring improved observability and operational reliability