Data Analyst Job Market Analysis

Introduction

This project focuses on the data analyst job market, analyzing top-paying roles, in-demand skills, and the intersection of high demand and high salary in data analytics.

SQL Queries: Check out the raw SQL files here: project_sql folder

Background

I started this project to better navigate the data analyst job market. My goal was to pinpoint the highest-paid and most in-demand skills to help streamline the job search process for myself and others looking for optimal opportunities.

Key Questions Analyzed:

1. What are the highest-paying data analyst roles?
2. Which skills are required for these top-paying jobs?
3. What are the most in-demand skills for data analysts?
4. Which skills are associated with higher salaries?
5. What are the most optimal skills to learn (High Demand + High Salary)?

Tools Used

To analyze the data analyst job market, I used the following tools:

• SQL: The core of my analysis, used to query the database and extract insights.
• PostgreSQL: The database management system used to handle the job posting data.
• Visual Studio Code: My tool for database management and executing SQL queries.
• Git & GitHub: Used for version control and sharing my SQL scripts and analysis.

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The Analysis

Each query below targets a specific aspect of the data analyst job market.

1. Top Paying Data Analyst Jobs

To identify the highest-paying roles, I filtered data analyst positions by average yearly salary and location, specifically focusing on remote jobs. This highlights the best financial opportunities in the field.

SELECT 
    job_id,
    job_title,
    job_location,
    job_posted_date,
    job_schedule_type,
    salary_year_avg,
    name AS company_name
FROM job_postings_fact
LEFT JOIN company_dim ON company_dim.company_id = job_postings_fact.company_id
WHERE job_title_short = 'Data Analyst'
    AND job_location = 'Anywhere'
    AND salary_year_avg IS NOT NULL -- Excluded data without salary info for accurate ranking
ORDER BY salary_year_avg DESC
LIMIT 10;

Insights:

• Wide Salary Range: The top 10 remote data analyst roles span from $184,000 to $650,000.

• Diverse Employers: Companies like SmartAsset, Meta, and AT&T are offering these top salaries.

• Job Title Variety: Titles range from standard "Data Analyst" to "Director of Analytics."

2. Skills for Top Paying Jobs

To understand what skills are required for these high-paying roles, I joined the job postings with the skills data. Note: I renamed the CTE to top_10_remote_jobs for clarity.

WITH top_paying_skills AS (
    SELECT job_id,
        job_title,
        job_schedule_type,
        salary_year_avg,
        name AS company_name
    FROM job_postings_fact
        left JOIN company_dim ON company_dim.company_id = job_postings_fact.company_id
    WHERE job_title_short = 'Data Analyst'
        AND job_location = 'Anywhere'
        AND salary_year_avg IS NOT NULL
    ORDER BY salary_year_avg DESC
    LIMIT 10
)
SELECT top_paying_skills.*,
    skills
FROM top_paying_skills
    INNER JOIN skills_job_dim ON top_paying_skills.job_id = skills_job_dim.job_id
    INNER join skills_dim ON skills_dim.skill_id = skills_job_dim.skill_id
ORDER BY salary_year_avg DESC

Insights:

• SQL is leading with a bold count of 8.
• Python follows closely with a bold count of 7.
• Tableau is also highly sought after, with a bold count of 6. Other skills like R, Snowflake, Pandas, and Excel show varying degrees of demand.

3. In-Demand Skills for Data Analysts

This query identifies the skills most frequently requested in job postings, showing where job seekers should focus their learning.

SELECT 
    skills,
    COUNT(skills_job_dim.job_id) AS demand_count
FROM 
    job_postings_fact
INNER JOIN skills_job_dim ON skills_job_dim.job_id = job_postings_fact.job_id
INNER JOIN skills_dim ON skills_dim.skill_id = skills_job_dim.skill_id
WHERE 
    job_title_short = 'Data Analyst'
GROUP BY 
    skills
ORDER BY 
    demand_count DESC
LIMIT 5;

Insights:

SQL and Excel remain the foundational skills for data processing. Python, Tableau, and Power BI are essential for technical analysis and visualization.

Skills	Demand Count
SQL	7291
Excel	4611
Python	4330
Tableau	3745
Power BI	2609

Table of the demand for the top 5 skills in data analyst job postings

4. Skills Based on Salary

This query explores the average salaries associated with different skills to identify which technical expertise commands the highest pay.

SELECT skills,
    ROUND(AVG(job_postings_fact.salary_year_avg), 0) AS avg_salary
FROM job_postings_fact
    INNER JOIN skills_job_dim ON skills_job_dim.job_id = job_postings_fact.job_id
    INNER JOIN skills_dim ON skills_dim.skill_id = skills_job_dim.skill_id
WHERE job_title_short = 'Data Analyst'
    AND salary_year_avg IS NOT NULL
    AND job_work_from_home = True
GROUP BY skills
ORDER BY avg_salary DESC
LIMIT 10;

Insights:

• Big Data & ML: Top earners specialize in tools like PySpark, Couchbase, and DataRobot.
• Engineering Crossover: Knowledge of GitLab, Kubernetes, and Airflow (typically engineering tools) commands a premium.
• Cloud Tools: Proficiency in Elasticsearch and Databricks is highly valued.

Skills	Average Salary ($)
pyspark	208,172
bitbucket	189,155
couchbase	160,515
watson	160,515
datarobot	155,486
gitlab	154,500
swift	153,750
jupyter	152,777
pandas	151,821
elasticsearch	145,000

Table of the average salary for the top 10 paying skills for data analysts

5. Most Optimal Skills to Learn

This query combines demand and salary data to find the "sweet spot" skills—those that are high in demand and offer high salaries.

WITH skill_demand_counts AS (
    SELECT 
        skills_dim.skill_id,
        skills_dim.skills,
        COUNT(skills_job_dim.job_id) AS demand_count
    FROM 
        job_postings_fact
    INNER JOIN skills_job_dim ON skills_job_dim.job_id = job_postings_fact.job_id
    INNER JOIN skills_dim ON skills_dim.skill_id = skills_job_dim.skill_id
    WHERE 
        job_title_short = 'Data Analyst'
        AND job_work_from_home = TRUE
        AND salary_year_avg IS NOT NULL
    GROUP BY 
        skills_dim.skill_id
), 
skill_avg_salaries AS (
    SELECT 
        skills_job_dim.skill_id,
        ROUND(AVG(job_postings_fact.salary_year_avg), 0) AS avg_salary
    FROM 
        job_postings_fact
    INNER JOIN skills_job_dim ON skills_job_dim.job_id = job_postings_fact.job_id
    INNER JOIN skills_dim ON skills_dim.skill_id = skills_job_dim.skill_id
    WHERE 
        job_title_short = 'Data Analyst'
        AND job_work_from_home = TRUE
        AND salary_year_avg IS NOT NULL
    GROUP BY 
        skills_job_dim.skill_id
)

SELECT 
    skill_demand_counts.skill_id,
    skill_demand_counts.skills,
    demand_count,
    avg_salary
FROM 
    skill_demand_counts
INNER JOIN skill_avg_salaries ON skill_demand_counts.skill_id = skill_avg_salaries.skill_id
WHERE 
    demand_count > 10
ORDER BY 
    avg_salary DESC, 
    demand_count DESC
LIMIT 25;

Skill ID	Skills	Demand Count	Average Salary ($)
8	go	27	115,320
234	confluence	11	114,210
97	hadoop	22	113,193
80	snowflake	37	112,948
74	azure	34	111,225
77	bigquery	13	109,654
76	aws	32	108,317
4	java	17	106,906
194	ssis	12	106,683
233	jira	20	104,918

Table of the most optimal skills for data analyst sorted by salary (Displayed top 10)

Insights:

• Cloud & Big Data: Skills like Snowflake, Azure, AWS, and Hadoop are high-value.
• Programming: Java and Go offer high salaries but lower demand compared to Python.
• Tools: Jira and Confluence knowledge is surprisingly lucrative.

What I Learned

Throughout this project, I strengthened my SQL skills in the following areas:

1. Complex Query Construction: I mastered advanced SQL techniques, including complex joins and CTEs.
2. Data Aggregation: I utilized GROUP BY and aggregate functions like COUNT() and AVG() to summarize data effectively.
3. Analytical Problem Solving: I translated real-world business questions into actionable SQL queries.

Conclusion

Insights

From the analysis, several general insights emerged:

1. Top-Paying Data Analyst Jobs: Remote data analyst roles show a significant salary spread, with top positions reaching compensation levels as high as $650,000, highlighting the earning potential at senior and specialized levels.

2. Skills for Top-Paying Jobs: High compensation data analyst roles consistently emphasize strong expertise in SQL, reinforcing its importance as a core skill for accessing top tier salaries.

3. Most In-Demand Skills: SQL emerges as the most frequently requested skill across job postings, making it a foundational requirement for aspiring and experienced data analysts alike.

4. Skills with Higher Salaries: Niche and specialized technologies such as SVN and Solidity command higher average salaries, reflecting a market premium for rare and specialized skill sets.

5. Optimal Skills for Job Market Value: With both high demand and strong salary outcomes, SQL stands out as one of the most valuable skills for data analysts aiming to maximize their competitiveness in the job market.

Credits & Inspiration

This project was developed following Luke Barousse’s SQL for Data Analytics course. All queries, analysis, and outputs were implemented as demonstrated in the video and reflect the tutorial work.