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

I need a Python developer to build an automated real estate market intelligence pipeline that collects publicly available listing data from major US real estate platforms (Redfin, Zillow, Realtor.com), 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 (no scraping needed) 2. Uses Redfin's internal Stingray JSON API endpoints to pull zip-level data 3. Uses Apify pre-built actors for Zillow and Realtor.com data collection 4. Calculates a 'pending percentage' metric per zip code from both sources 5. Cross-references both sources and flags agreement/disagreement 6. Scores each zip code using a weighted composite model 7. Identifies distressed properties within high-scoring zip codes 8. Outputs a daily ranked target list to Airtable with Slack alerts TECH STACK (required experience)- Python 3.10+- Playwright (browser automation for JavaScript-rendered pages)- Apify platform (pre-built actors + scheduling)- Airtable API (data storage and output)- Google Sheets API (dashboard output)- Slack Webhooks (alert notifications)- Async Python (asyncio) for parallel data collection- Residential proxy integration (Smartproxy or Decodo) DELIVERABLES Milestone 1 ($200): Core data collection pipeline- Python script that downloads Redfin Data Center CSV- Script that hits Redfin Stingray API for zip-level active + pending counts- Pending percentage calculation per zip code - Output to Google Sheets Milestone 2 ($250): Apify integration + cross-referencing- Configure Apify Zillow Search Scraper actor for same zip codes- Build corroboration logic (both sources agree within 5% = confirmed)- Configure Apify Realtor.com actor as tiebreaker source- Write corroboration results to Airtable Milestone 3 ($200): Distressed property identification- Build keyword-based distress scoring on listing descriptions- Identify properties with high DOM, price reductions, relisted status- Flag assignment vs novation candidates- Write scored properties to Airtable 'Target Properties' table\ Milestone 4 ($150): Scheduling, alerts, and documentation- Set up Apify 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)- Apify account credentials- Proxy service credentials (Smartproxy or Decodo) IDEAL FREELANCER- 90%+ Job Success Score on Upwork- Proven experience with Playwright or Puppeteer web data collection- Experience with Apify platform (actors, scheduling, datasets)- Experience with Airtable API integration- Has built data pipelines that run on schedule without manual intervention- Bonus: experience with real estate data or Redfin/Zillow specifically TO APPLY In your proposal, please answer these three questions: 1. Have you built a Playwright-based data collection pipeline before? If so, briefly describe the project. 2. Have you used the Apify platform? If not, are you willing to learn it (it has excellent documentation)? 3. What is your estimated timeline to deliver all 4 milestones? Please do not send generic proposals. I will only respond to proposals that answer these three questions specifically.