Python Developer — Real Estate Market Intelligence Data Pipeline (Playwright + Apify + Airtable)

Summary I need a Python developer to build an automated real estate market intelligence pipeline that collects publicly available housing market data from major US real estate data providers, calculates market health metrics per zip code, and outputs a ranked daily target list to Airtable. This is a fixed-price project with clear milestones and deliverables. WHAT THE SYSTEM DOES 1. Downloads free public CSV data from Redfin Data Center. 2. Retrieves additional ZIP-level market data from approved data sources. 3. integrates additional housing market data providers for cross-source validation. 4. Calculates a "pending percentage" metric per ZIP code from multiple sources. 5. Cross-references both sources and flags agreement/disagreement. 6. Scores each ZIP code using a weighted composite model. 7. Identifies investment opportunities within high-scoring ZIP codes using configurable scoring logic. 8. Outputs a daily ranked target list to Airtable with Slack alerts. TECH STACK (required experience) Python 3.10+ Playwright (browser automation) REST API integrations Airtable API (data storage and output) Google Sheets API (dashboard output) Slack Webhooks (alert notifications) Async Python (asyncio) for parallel data collection Experience integrating third-party data providers Experience building scheduled ETL/data pipelines DELIVERABLES Milestone 1 ($200): Core data collection pipeline Python script that downloads Redfin Data Center CSV Script that retrieves ZIP-level active and pending market metrics from approved data sources Pending percentage calculation per ZIP code Output to Google Sheets Milestone 2 ($250): Multi-source integration + cross-referencing Integrate secondary housing market data source for the same ZIP codes Build corroboration logic (both sources agree within 5% = confirmed) Integrate an additional market data source for validation when needed Write corroboration results to Airtable Milestone 3 ($200): Investment opportunity identification Build keyword-based investment scoring on listing descriptions Identify properties with high DOM, price reductions, relisted status, and other configurable indicators Classify opportunities using configurable scoring rules Write scored properties to Airtable "Target Properties" table Milestone 4 ($150): Scheduling, alerts, and documentation Configure automated scheduling (daily, weekly, monthly cadences) Configure Slack webhook alerts for new hot markets and priority properties Build daily call list view in Airtable sorted by composite score Write setup documentation so I can maintain the system independently Total budget: $800 fixed price across 4 milestones Timeline: 2 weeks WHAT I PROVIDE Detailed technical specification document with every agent's logic List of target ZIP codes to start with Airtable base structure (I will create the tables) Credentials for any approved third-party services used by the project Any additional documentation required for implementation IDEAL FREELANCER 90%+ Job Success Score on Upwork Proven experience with Playwright, Puppeteer, or similar browser automation frameworks Experience building Python ETL/data pipelines Experience with Airtable API integration Has built automated systems that run on schedule without manual intervention Bonus: experience with real estate data, market analytics, or property technology platforms