Data Engineer / Web Scraper – Hospitality Market Intelligence (
Budget: $30 – $250 USD
Job Title: Data Engineer / Web Scraper – Hospitality Market Intelligence (SEA & MENA Regions)
Project Overview
We are seeking a highly skilled Data Engineer or Web Scraping Specialist to extract and compile a comprehensive dataset of hotel pricing and amenities across five key markets: Malaysia, Indonesia, Vietnam, Turkey, and the UAE.
The goal is to feed our AI system with high-granularity, historical, and forward-looking data to analyze competitive pricing trends and ancillary service costs.
Scope of Work
You will be responsible for sourcing or scraping a dataset covering a 2-month window (historical + forward-looking) with daily-rate granularity.
1. Core Data Requirements
Geographic Focus: Comprehensive coverage for Malaysia, Indonesia, Vietnam, Turkey, and UAE.
Competitor Benchmarking: Rates must be structured to allow direct comparison between similar hotel tiers/locations.
Granular Room Details: Pricing must be broken down by Room Type (e.g., Standard, Deluxe, Suite).
2. Ancillary & Metadata Points (Critical)
Beyond standard ADR (Average Daily Rate), we require the following specific data points:
Extra Bed Costs: Surcharges for additional guests/beds per room type.
Breakfast Pricing: Individual costs for breakfast if not included in the base rate.
Inventory Attributes: Identification/flags for hotels offering Connected Rooms.
Technical Requirements
Data Format: Cleaned, structured delivery in CSV, JSON, or direct SQL upload.
Source Reliability: Data must be sourced from reputable OTAs (e.g., Booking.com, Agoda, Expedia) or Global Distribution Systems (GDS).
Frequency: Ability to provide a one-time historical dump with a mechanism for potential future updates.
Ideal Candidate Profile
Proven experience in large-scale web scraping (Python, Scrapy, Selenium, or Puppeteer).
Familiarity with bypassing anti-bot measures (residential proxies, headless browsers).
Prior experience with hospitality or travel industry data is a significant plus.
Strong understanding of data normalization (ensuring "Deluxe Room" in Hotel A is comparable to "Deluxe Room" in Hotel B).
How to Apply
Please provide:
A brief description of your experience with hospitality data or complex scraping projects.
Your proposed tools/stack for this project.
A rough estimate of the timeline for data delivery for the specified regions.
(Optional) If you already have access to a proprietary database or API that covers these regions, please specify.
Project Overview
We are seeking a highly skilled Data Engineer or Web Scraping Specialist to extract and compile a comprehensive dataset of hotel pricing and amenities across five key markets: Malaysia, Indonesia, Vietnam, Turkey, and the UAE.
The goal is to feed our AI system with high-granularity, historical, and forward-looking data to analyze competitive pricing trends and ancillary service costs.
Scope of Work
You will be responsible for sourcing or scraping a dataset covering a 2-month window (historical + forward-looking) with daily-rate granularity.
1. Core Data Requirements
Geographic Focus: Comprehensive coverage for Malaysia, Indonesia, Vietnam, Turkey, and UAE.
Competitor Benchmarking: Rates must be structured to allow direct comparison between similar hotel tiers/locations.
Granular Room Details: Pricing must be broken down by Room Type (e.g., Standard, Deluxe, Suite).
2. Ancillary & Metadata Points (Critical)
Beyond standard ADR (Average Daily Rate), we require the following specific data points:
Extra Bed Costs: Surcharges for additional guests/beds per room type.
Breakfast Pricing: Individual costs for breakfast if not included in the base rate.
Inventory Attributes: Identification/flags for hotels offering Connected Rooms.
Technical Requirements
Data Format: Cleaned, structured delivery in CSV, JSON, or direct SQL upload.
Source Reliability: Data must be sourced from reputable OTAs (e.g., Booking.com, Agoda, Expedia) or Global Distribution Systems (GDS).
Frequency: Ability to provide a one-time historical dump with a mechanism for potential future updates.
Ideal Candidate Profile
Proven experience in large-scale web scraping (Python, Scrapy, Selenium, or Puppeteer).
Familiarity with bypassing anti-bot measures (residential proxies, headless browsers).
Prior experience with hospitality or travel industry data is a significant plus.
Strong understanding of data normalization (ensuring "Deluxe Room" in Hotel A is comparable to "Deluxe Room" in Hotel B).
How to Apply
Please provide:
A brief description of your experience with hospitality data or complex scraping projects.
Your proposed tools/stack for this project.
A rough estimate of the timeline for data delivery for the specified regions.
(Optional) If you already have access to a proprietary database or API that covers these regions, please specify.