Introduction

📊 Dive into the data job market! Focusing on data analyst roles, this project explores 💰 top-paying jobs, 🔥 in-demand skills, and 📈 where high demand meets high salary in data analytics.

🔎 SQL queries? Check them out here: project_sql folder

Background

Driven by a quest to navigate the data analyst job market more effectively, this project was born from a desire to pinpoint top-paid and in-demand skills, streamlining others' work to find optimal jobs.

This data hails from Luke Barousse's data website. It's packed with insights on job titles, salaries, locations, and essential skills.

The questions I wanted to answer through my SQL queries were:

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

Tools I Used

For my deep dive into the data analyst job market, I harnessed the power of several key tools:

• SQL: The backbone of my analysis, allowing me to query the database and unearth critical insights.
• PostgreSQL: The chosen database management system, ideal for handling the job posting data.
• Visual Studio Code: My go-to for database management and executing SQL queries.
• Git & Github: Essential for version control and sharing my SQL scripts and analysis, ensuring collaboration and project tracking.

The Analysis

Each query for this project aimed at investigating specific aspects fo the data analyst job market. Here's how I approached each question:

1. Top Paying Data Analyst Jobs

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

SELECT
  job_id,
  job_title,
  job_location,
  job_schedule_type,
  salary_year_avg,
  job_posted_date,
  cd.name AS company_name
FROM job_postings_fact jp
INNER JOIN company_dim cd
ON cd.company_id = jp.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;

Here's a breakdown of the top data anlyst jobs up to June 30, 2025:

• Wide Salary Range: Top-end remote analyst salaries exceed $600K, with the highest paid role being a standard “Data Analyst” at Mantys ($650K), showing that remote compensation can reach Silicon-Valley executive levels when tied to high-growth or specialized companies.

• Netflix dominates the top tier, consistently offering ~$445K for Analytics Engineer (L5) roles — indicating that “analytics engineer” titles command much higher pay than traditional data analyst positions, especially at tech giants.

• Job Title Variety: Director-level data roles (Meta, Confluent, AT&T) also appear with salaries between ~$255K–$336K, showing that remote leadership positions in analytics remain highly compensated and accessible without geographical restriction.

Bar graph visualizing the salary for the top 10 salaries for data analysts; ChatGPT generated this graph from my SQL query results

2. Skills for Top Paying Jobs

To understand what skills are required for the top-paying jobs, I joined the job postings with the skills data, providing insights into what employers value for high-compensation roles.

WITH top_paying_jobs AS (
  SELECT
    jp.job_id,
    job_title,
    salary_year_avg,
    cd.name AS company_name
  FROM job_postings_fact jp
  INNER JOIN company_dim cd ON cd.company_id = jp.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_jobs.*,
  sd.skills as skill_name
FROM top_paying_jobs
INNER JOIN skills_job_dim sjd ON sjd.job_id = top_paying_jobs.job_id
INNER JOIN skills_dim sd ON sd.skill_id = sjd.skill_id
ORDER BY top_paying_jobs.salary_year_avg DESC;

Here's a quick breakdown of the skills listed for top-paying roles:

• SQL and Python dominate high-salary roles - this shows top-earning analysts are expected to handle data querying + advanced analysis or automation

• Tableau stands out among specialized tools showing companies pay more for analysts who can present insights clearly.

• Cloud / data engineering skills show up consistently, suggesting that analysts who can work with modern data pipelines and distributed systems command higher pay.

Bar graph visualizing the count of the top 10 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 skilsl most frequently requested in job postings, directing focus to areas with high demand.

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

Here's a breakdown of the most demanded skills for data analysts (up to June 30, 2025):

• SQL is the single most in-demand skill for data analysts
• Excel remains extremely strong, even above Python, emphasizing the need for strong foundational skills in spreadsheet manipulation
• Python, Tableau, and Power BI round out the top-5, showing that analysts need both programming + visualization + spreadsheet skills

Skill	Demand Count
sql	180369
excel	131822
python	116082
tableau	90588
power bi	84353

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

4. Skills Based on Salary

Exploring the average salaries associated with different skills revealed which skills are the highest paying.

SELECT
  sd.skills AS skill,
  ROUND(AVG(jp.salary_year_avg),0) AS avg_salary
FROM job_postings_fact jp
INNER JOIN skills_job_dim sjd ON sjd.job_id = jp.job_id
INNER JOIN skills_dim sd ON sd.skill_id = sjd.skill_id
WHERE (
  jp.job_title_short = 'Data Analyst' AND
  jp.salary_year_avg IS NOT NULL
  )
GROUP BY skill
ORDER BY avg_salary DESC
LIMIT 25;

Here's a quick breakdown of the results for the top paying skills based on salary:

• The highest-paying skills skew toward software engineering & backend frameworks (FastAPI, Blazor, ASP.NET Core, React.js, Golang), showing that “analytics engineers” earn substantially more than dashboard/reporting analysts.

• Cloud, NoSQL, and infrastructure tools like DynamoDB, Terraform, ElasticSearch, and Neo4j appear frequently — signaling that companies pay more for analysts who work with big data pipelines and distributed systems.

• AI/ML-focused technologies such as Hugging Face, MXNet, Watson, and GraphQL provide a salary boost, suggesting that analysts who support machine learning workflows fall into the top earning tier.

Skills	Average Salary ($)
fastapi	212500
svn	185000
blazor	161000
apl	155000
mxnet	149000
graphql	137699
typescript	135520
asp.net core	130500
dynamodb	129970
solidity	128313

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

5. Most Optimal Skills to Learn

Combining insights from demand and salary data, this query aimed to pinpoint skills that are both in high demand and have high salaries, offering a strategic focus for skill development.

SELECT
    sd.skill_id,
    sd.skills AS skill,
    count(sjd.job_id) AS demand_count,
    ROUND(AVG(jp.salary_year_avg),0) AS average_salary
FROM job_postings_fact jp
INNER JOIN skills_job_dim sjd ON sjd.job_id = jp.job_id
INNER JOIN skills_dim sd ON sd.skill_id = sjd.skill_id
WHERE
    jp.job_title_short = 'Data Analyst' AND
    jp.job_work_from_home = TRUE AND
    jp.salary_year_avg IS NOT NULL
GROUP BY
    sd.skill_id
HAVING count(sjd.job_id) > 10
ORDER BY
    demand_count DESC,
    average_salary DESC
LIMIT 25;

Skill ID	Skills	Demand Count	Average Salary ($)
0	sql	783	98748
183	tableau	505	102172
1	python	494	98074
184	excel	441	88202
186	power bi	293	95535
2	r	289	97421
185	looker	117	94281
8	sas	110	94101
194	sas	110	94101
198	powerpoint	97	88567

Table of the most optimal skills for data analysts sorted by salary

Here's a breakdown of the most optimal skills for Data Analysts (up to June 30, 2025):

• SQL, Tableau, Python, and Excel dominate demand, showing that the core analyst toolset still revolves around querying, scripting, visualization, and spreadsheet analysis.

• Cloud data warehouse skills (Snowflake, AWS, BigQuery, Redshift, Azure) appear throughout the dataset, signaling that analysts are expected to interact with modern data pipelines and distributed data systems, not just spreadsheets.

• Some low-demand skills carry very high average salaries like Zoom ($139K) and Go ($121K), which can suggest that niche technical expertise or cross-functional tooling can command premium pay.

What I Learned

Throughout this adventure, I've turbocharged SQL toolkit with some serious firepower:

• 🧩 Complex Query Crafting: Mastered the art of advanced SQL, merging tables like a pro and wielding WITH clauses for ninja-level temp table maneuvers.
• 📊 Data Aggregation: Got comfortable with GROUP BY and turned aggregate functions like COUNT() and AVG() into my data-summarizing sidekicks.
• 💡 Analytical Wizardry: Leveled up my real-word puzzle-solving skills, turning questions into actionable, insightful SQL queries.

Conclusions

Insights

1. Top-Paying Data Analyst Jobs: The highest-paying data analyst jobs that allow remote work offer a wide range of salaries. The highest at $650,000!
2. Skills for Top-Paying Jobs: High-paying data analyst jobs require advanced proficiency in SQL, indicating that it's a critical skill for earning a top salary.
3. Most In-demand Skills: SQL is also the most in-demand skill in the data analyst job market. Making it essential for job seekers like me.
4. Skills with Higher Salaries: Specialized skills, such as FastAPI and SVN, are associated with the highest average salaries, indicating a premium on niche expertise.
5. Optimal Skills for Job Market Value: SQL leads in demand and offers a high average salary, positioning it as one of the most optimal skills for data analysts to learn to maximize their market value.

Closing Thoughts

This project enhanced my SQL skills and provided valuable insights into the data analyst job market. The findings from the analysis serve as a guide to prioritizing skill development and job search efforts. Aspiring data analysts, like myself, can better position themselves in a competitive job market by focusing on high-demand, high-salary skills. This exploration highlights the importance of continuous learning and adaptation to emerging trends in the field of data analytics.