SQL Data Automation Workflow

I need an end-to-end data automation solution that connects directly to my SQL databases, extracts the required tables on a schedule, transforms the data to a clean analytics-ready format, and deposits the results into a target store I can easily query or feed into BI dashboards.

Here is what I’m expecting:
• Connection and authentication set-up for multiple SQL instances (mostly PostgreSQL and MySQL).
• A repeatable ETL/ELT pipeline written in Python, SQL scripts, or a modern orchestration tool such as Airflow, Prefect, or dbt—whichever you’re most comfortable with.
• Parameter-driven jobs so I can adjust table lists, filters, or load frequency without touching the code.
• Logging, basic alerting, and clear documentation so future maintenance is straightforward.
• A quick hand-off session (video or screen share) to walk me through running, monitoring, and updating the workflow.

Acceptance criteria
1. A single command or scheduled trigger reliably pulls fresh data and completes without manual intervention.
2. All transformations execute inside the pipeline; no ad-hoc spreadsheet work should be needed.
3. Logs clearly flag errors and successes and are stored in a location I specify.
4. Documentation includes setup steps, environment variables, and a diagram of the process.

If you’ve built similar SQL-centric automation, especially using open-source tooling, I’d love to see a brief example or repo link when you reply.