Can I vibe code Adverity?

Build a python-based ETL pipeline script for ecommerce marketing data using FastAPI, DuckDB, and PostgreSQL.

1. DATA INGESTION & CONNECTORS:
- Build extraction modules for Shopify GraphQL API (orders, customers, line items) and Meta Ads Insights REST API (impressions, clicks, spend, campaign ID).
- Implement OAuth2 token refresh handlers and rate-limit handling with exponential backoff for both APIs.
- Save raw JSON responses directly into an append-only raw_ingestion table in PostgreSQL with timestamp and source labels.

2. TRANSFORMATION ENGINE:
- Use DuckDB in-memory to query raw JSON from PostgreSQL.
- Normalize ad spend, impressions, clicks, and revenue into a unified daily analytics table: unified_daily_performance(date, channel, campaign_id, spend, impressions, clicks, revenue, orders).
- Include currency conversion to USD based on daily static exchange rates.

3. ERROR HANDLING & SCHEMAS:
- Implement schema validation on incoming JSON payloads using Pydantic.
- If incoming JSON fields deviate or miss required attributes, log to an ingestion_errors table and fire a Slack notification webhook without failing the entire sync job.

4. SCHEDULER & DASHBOARD:
- Schedule daily sync jobs at 02:00 UTC using APScheduler.
- Expose a simple FastAPI dashboard showing sync status, total rows processed, failed jobs, and aggregated spend vs revenue graphs using Chart.js.

OUT OF SCOPE: Third-party analytics connectors outside Shopify and Meta Ads, complex multi-tenant enterprise RBAC.

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