Source pulls
Python ETL scripts collect Google Ads, Meta Ads, Sheets inputs, and event-tracking data.
Custom marketing dashboard combining Google Ads, Facebook Ads, Google Sheets, BigQuery-style reporting, and event tracking components.

System architecture
The practical path from source data to reliable reporting output.
Python ETL scripts collect Google Ads, Meta Ads, Sheets inputs, and event-tracking data.
Warehouse-style tables are exposed through dashboard API routes for controlled query access.
A Next.js app presents authenticated filters, grids, charts, and reporting views.
Platform exports, source ranges, and event payloads are reconciled before the UI becomes the source of truth.
Built a custom marketing reporting application where platform pulls, warehouse tables, dashboard queries, and UI views had to work as one system. The project combined Python ETL scripts for Google Ads, Facebook Ads, and Sheets data with a Next.js dashboard, BigQuery-facing API routes, and event tracking components.
If your reporting process depends on APIs, spreadsheets, ad platforms, or asynchronous exports, I can help turn it into a reliable pipeline with validation, monitoring, and clean outputs.