Automation & Data Engineering
Salary Benchmarking via Web Scraping — Python
Collected market salary data for 100+ positions automatically with Selenium
The Problem
The company needed to assess whether practiced salaries were market-aligned and define realistic salary ranges for new positions. With over 100 different positions, manually researching the average salary for each position on public platforms would be extremely time-consuming, repetitive, and not scalable.
The Solution
I developed a Python script with Selenium that reads a base with a list of positions, performs automatic searches on the salary platform (Glassdoor), extracts the corresponding average salary for each position, and generates a structured CSV file for analysis. The solution uses dynamic web scraping due to dynamic page components.
Tech Stack
Impact Generated
- Significant savings in HR operational time
- Reduced risk of opening positions with off-market salaries
- Improved position acceptance rate
- Direct support for HR and Finance decision-making
- Support for competitive salary definition
Positions Researched
100+
Execution
Manual and on-demand
Users
HR, Finance Management
Tech Stack
Overview
Automation,
Data Engineering
Technical Stack
Technical Challenges
- First practical contact with web scraping
- Using Selenium to handle dynamic pages
- Treatment of automatically collected data
- Dealing with external platform limitations