Build MySQL Data Integration Pipeline

I need a robust end-to-end data pipeline that reliably pulls data from two main sources—our MySQL transactional database and several third-party APIs—and lands it in a clean, query-ready store. The primary objectives are to automate ingestion, ensure data quality through basic validation checks, and make the transformed data available on a predictable schedule for our analytics team.

Here’s how I picture the workflow:
1. Ingestion
• Incremental extracts from MySQL (binlog or timestamp strategy).
• Scheduled API calls with rate-limit awareness and retry logic.
2. Transformation & Validation
• Lightweight cleansing, type casting, and schema enforcement.
• Simple anomaly detection (row counts, null checks) with alerting.
3. Orchestration & Monitoring
• Prefer Airflow or an equivalent orchestrator; I’m open if you have a better suggestion.
• Logging and dashboarding so failures are surfaced quickly.
4. Delivery
• Output as parquet or CSV in an S3-compatible bucket, partitioned by date.

Acceptance criteria
• A reproducible codebase (Python is ideal) in a Git repo with README.
• Parameterised configs so changing environments or credentials is straightforward.
• One-click deployment instructions (Docker compose or Terraform welcomed).
• A successful dry-run on sample data that demonstrates the pipeline end to end.

Let me know which pieces you’d tackle first, the toolset you recommend, and how quickly you can have an initial version ready.