Project

Overview

This project analyzes the data analyst job market with a focus on identifying top-paying roles, in-demand skills, and the intersection between high demand and high salary. Using real-world job posting data from a SQL course by Luke Barousse, the analysis addresses questions such as which data analyst jobs pay the most, what skills those roles require, which skills are most frequently requested by employers, and which skills are associated with higher salaries. The dataset includes detailed information on job titles, salaries, locations, and required skills. All analysis was performed using SQL with PostgreSQL as the database engine, Visual Studio Code for query execution, and Git and GitHub for version control and documentation. As part of the technical scope, the entire project was containerized using Docker and published to Docker Hub as hands-on practice with containerization and image distribution.

Through a series of targeted SQL queries, the project shows that remote data analyst roles can offer a very wide salary range, with top positions reaching exceptionally high compensation levels. Advanced SQL emerges as both a core requirement for high-paying roles and the most in-demand skill overall, making it essential for aspiring data analysts. Additionally, skills related to cloud platforms, big data technologies, machine learning tools, and data engineering workflows are strongly associated with higher average salaries, reflecting the increasing convergence of analytics and engineering. Beyond the analytical findings, dockerizing and publishing the project reinforced practical experience in deploying reproducible, portable data projects, while the overall work strengthened advanced SQL skills and provided clear, actionable guidance for prioritizing skill development in a competitive job market.