Lead Gen Automation Pipeline Build

I’m building a fully-automated lead generation engine and need an engineer who can wire everything together end-to-end. The core flow pulls prospects from Clodo, enriches them with Clay, sequences outreach through Apollo, syncs engagement data back to HubSpot, and surfaces every scored lead in a dedicated Slack channel. All of these services expose solid REST/GraphQL APIs, so the job is primarily about clean JSON handling and resilient workflow orchestration.

Key functions I want in place:
• Email outreaches, data enrichment, plus lead scoring and routing run automatically on every new record.
• GitHub Actions triggers and monitors the pipeline, with Python scripts responsible for transformation, enrichment and retry logic.
• Each step posts concise status and error messages to Slack so I can track performance in real time.

Deliverables:
1. Well-documented Python code that calls Clodo, Clay, Apollo and HubSpot APIs, parses their JSON payloads, and normalizes data for downstream steps.
2. A GitHub Actions workflow file that installs dependencies, executes the Python jobs, and persists state/logs securely.
3. Slack integration that pushes notifications for: successful enrichment, outreach sent, score threshold met, and any failed task.
4. README covering environment variables, secrets management, and instructions for extending the pipeline to new tools.

Acceptance criteria:
• A sample batch of leads runs through the entire pipeline in under 10 minutes with zero manual intervention.
• Lead score ≥ defined cutoff automatically appears in Slack with all enrichment fields.
• On simulated API failure the job retries gracefully and posts a clear error summary.

If you have previous experience stitching SaaS APIs together and deploying via GitHub Actions, I’d like to review a brief outline of your proposed approach and timeline.