Mapping the Data Analyst Job Market with SQL
- James Gifford
- Jun 24
- 5 min read
Updated: Oct 10
This project dives into the data analyst job market to uncover which skills are most in demand and which roles offer the highest salaries. By analyzing real job posting data, I aimed to find where high demand meets high pay—helping both myself and others target the right skills for breaking into data analytics.
Background
As I transition into data analytics, this project helped me pinpoint top-paying roles and high-demand skills, cutting through the noise to focus on what actually matters when landing a job.
The data comes from Luke Barousse’s SQL for Data Analytics course, which includes job titles, salaries, locations, and technical skills.
The questions I wanted to answer through my SQL queries were:
What are the top-paying data analyst jobs?
What skills do these top-paying jobs require?
Which skills are most in demand for data analysts?
What skills tend to lead to higher salaries?
What are the most optimal skills for me to learn?
Tools Used
SQL (PostgreSQL): for writing queries and cleaning data
VS Code: to run and iterate on queries
GitHub: for tracking and sharing my work
ChatGPT: to quickly generate charts from SQL query results
Key Insights
Each SQL query in this project explored a different aspect of the data analyst job market, answering practical questions that helped me align my skill development with high-demand roles.
💼 1. Top-Paying Data Analyst Jobs
I started by identifying the highest-paying data analyst roles. I filtered for jobs with non-null average yearly salaries and focused on remote positions, since that flexibility is important to me. This helped surface the most lucrative opportunities and gave me a benchmark for salary expectations in the field.
Here's the breakdown of the top data analyst jobs in 2023:
Wide Salary Range: The top 10 highest-paying data analyst roles range from $184,000 to $650,000, showing just how high the salary ceiling can be in this field.
Diverse Employers: Companies like SmartAsset, Meta, and AT&T are offering top compensation, highlighting strong demand across industries—from tech to finance to telecom.
Job Title Variety: High-paying roles span a wide spectrum of titles, from “Data Analyst” to “Director of Analytics,” reflecting the different levels of responsibility and specialization within the data analytics space.
🛠️ 2. Skills for Top-Paying Roles
To figure out what skills are actually required for the top-paying data analyst roles, I joined the job postings with the skills data. This helped me identify which tools and technologies employers are looking for when offering the highest salaries.
Here’s the breakdown of the most in-demand skills from the top 10 highest-paying data analyst jobs in 2023:
SQL is leading with a count of 8.
Python follows closely with a count of 7.
Tableau is also very sought after with a count of 6. Other skills like R, Snowflake, Pandas, and Excel show varying degrees of demand.
Bar graph visualizing the count of skills for the top 10 paying jobs for data analysts; ChatGPT generated this graph from my SQL query results
📈 3. In-Demand Skills for Data Analysts
This query helped identify the skills most frequently requested in job postings, directing focus to areas with high demand.
Here's the breakdown of the most in-demand skills for data analysts in 2023:
SQL and Excel lead, highlighting core skills in data querying and spreadsheets.
Tools like Python, Tableau, and Power BI show the growing demand for programming and data visualization.
💰4. Skills Based on Salary
Exploring the average salaries associated with different skills revealed which skills are the highest paying.
Here's a breakdown of the results for top-paying skills for Data Analysts:
High Demand for Big Data & ML Skills:
Top salaries are commanded by analysts skilled in big data technologies (PySpark, Couchbase), machine learning tools (DataRobot, Jupyter), and Python libraries (Pandas, NumPy), reflecting the industry's high valuation of data processing and predictive modeling capabilities.
Software Development & Deployment Proficiency:
Knowledge in tools like GitLab, Kubernetes, and Airflow shows a strong crossover between analysis and engineering, with a premium on automation and pipeline management skills.
Cloud Computing Expertise:
Familiarity with Elasticsearch, Databricks, and GCP highlights the growing demand for cloud-native analytics, suggesting that cloud proficiency significantly boosts earning potential.
🎯 5. Most Optimal Skills to Learn
To pinpoint the most strategic skills for career growth, I filtered for those that are both in high demand and tied to high average salaries in remote data analyst roles.
Based on my analysis of job postings, here's a breakdown of the most optimal skills to focus on as an aspiring data analyst:
High-Demand Programming Languages:
Python and R are consistently sought after, with demand counts of 236 and 148. While the average salaries for these are around $101,397 (Python) and $100,499 (R), their wide availability in the job market slightly levels out their earning potential. Still, they remain essential technical skills in any analyst’s toolkit.
Cloud Tools and Technologies:
Skills like Snowflake, Azure, AWS, and BigQuery show strong demand paired with above-average salaries. These tools are increasingly central to modern data analytics workflows, especially in cloud-first companies.
Business Intelligence & Visualization Tools:
Tableau (demand count: 230, avg. salary: $99,288) and Looker (demand count: 49, avg. salary: $103,795) reinforce the importance of being able to translate complex data into actionable insights through dashboards and visual storytelling.
Database Technologies:
Whether it's traditional systems like Oracle and SQL Server or modern NoSQL databases, these skills are still highly relevant. With salaries ranging from $97,786 to $104,534, database fluency supports both data integrity and access in analytics workflows.
🔍 What I Learned
This project sharpened my SQL skills while giving me a data-driven view of what employers actually value. I practiced joining multiple tables, writing WITH clauses to simplify logic, and using aggregation functions like GROUP BY, COUNT(), and AVG() to uncover trends.
More importantly, it helped me turn vague career advice into focused, measurable goals. I now have a clear direction on which skills to prioritize based on real market demand and salary potential.
🎯 Key Takeaways
💼 Top Roles Pay Big: Remote data analyst jobs can reach up to $650K, showing the upper limits of the field.
🛠️ SQL is Non-Negotiable: It's the most requested and best-paying core skill.
📈 Python, Tableau, Cloud Tools: These consistently rank high in both demand and pay.
💰 Niche Tools Pay More: Skills like PySpark, Databricks, and Jupyter are tied to top salaries.
🎯 Best ROI: SQL stands out as the most strategic skill, balancing high demand with strong salary potential.
By focusing on high-value, high-demand skills, I’m better equipped to target the right jobs and invest my learning time where it counts.
📈 Business Impact
This project translates job market data into actionable insights for aspiring and current analysts. By identifying which skills drive both demand and salary growth, it provides a clear framework for career planning and upskilling based on real market evidence.
It also demonstrates how SQL can uncover patterns that guide workforce development and hiring strategies across the data industry.
Comments