This project is a result of my learning journey through Luke Barousse's SQL Course. It focuses on exploring the data job market, particularly data analyst roles, by examining 💸 top-paying jobs, 🔥 in-demand skills, and where 📈 high demand meets high salaries.
SQL queries I practiced can be found here: project_sql
The insights and data in this project come from Luke Barousse’s course. My goal was to thoroughly understand and apply the concepts he taught, using his provided dataset to explore top-paying and in-demand skills for data analysts.
- What are the top-paying data analyst jobs?
- What skils are required for these top-paying jobs?
- What skills are most in demand for data analysts?
- Which skills are associated with higher salaries?
- What are the most optimal skills to learn?
Here are the tools I used while following the course:
-
SQL: The backbone of my analysis, allowing me to query the database and unearth critical insights.
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PostgreSQL: The chosen database management system, ideal for handling the job posting data.
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Visual Studio Code: My go-to for database management and executing SQL queries.
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Git & GitHub: Essential for version control and sharing my SQL scripts and analysis, ensuring collaboration and project tracking.
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ChatGPT & Julius AI: Valuable AI tools I used for generating insights, clarifying SQL concepts when I needed deeper understanding, and exploring ideas for visualizing data effectively. They acted as guides throughout my learning process, helping me better analyze and interpret the results.
Each query in this project follows the structure and methodology taught in the course. I practiced and adapted them to deepen my understanding.
To identify the highest-paying roles, I queried the data for average yearly salary and location, focusing on remote jobs. This exercise demonstrated how to highlight lucrative opportunities in the field.
SELECT
job_id,
job_title,
job_location,
job_schedule_type,
TO_CHAR(ROUND(salary_year_avg, 0), 'FM$999,999,999') AS avg_yearly_salary,
job_posted_date,
name AS company_name
FROM
job_postings_fact
LEFT JOIN company_dim
ON job_postings_fact.company_id = company_dim.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 the breakdown of the top data analyst jobs in 2023:
-
Wide Salary Range: Top 10 paying data analyst roles span from $184,000 to $650,000, indicating significant salary potential in the field.
-
Diverse Employers: Companies like SmartAsset, Meta, and AT&T are among those offering high salaries, showing a broad interest across different industries.
-
Job Title Variety: There's a high diversity in job titles, from Data Analyst to Director of Analytics, reflecting varied roles and specializations within data analytics.
Bar graph showcasing the top 10 highest-paying data analyst roles, generated by Julius AI using the results of my SQL query.
Using the dataset, I identified the skills most commonly associated with high-paying roles. This query revealed the technical competencies valued in the job market.
WITH top_paying_jobs AS (
SELECT
job_id,
job_title,
TO_CHAR(ROUND(salary_year_avg, 0), 'FM$999,999,999') AS avg_yearly_salary,
name AS company_name
FROM
job_postings_fact
LEFT JOIN company_dim ON job_postings_fact.company_id = company_dim.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.*,
skills_dim.skills
FROM
top_paying_jobs
INNER JOIN skills_job_dim ON top_paying_jobs.job_id = skills_job_dim.job_id
INNER JOIN skills_dim ON skills_job_dim.skill_id = skills_dim.skill_id
ORDER BY
avg_yearly_salary DESC;Here's the breakdown of the most demanded skills for the top 10 highest paying data analyst jobs in 2023:
-
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.
*Bar graph visualizing the frequency of skills required for the top 10 highest-paying data analyst jobs, generated by Julius AI from my SQL query results.
By analyzing the frequency of skills listed across all job postings, I highlighted the ones most sought after by employers.
SELECT
skills,
COUNT(skills_job_dim.job_id) AS demand_count
FROM job_postings_fact
INNER JOIN skills_job_dim ON job_postings_fact.job_id = skills_job_dim.job_id
INNER JOIN skills_dim ON skills_job_dim.skill_id = skills_dim.skill_id
WHERE
job_title_short = 'Data Analyst' AND
job_work_from_home IS TRUE
GROUP BY
skills
ORDER BY
demand_count DESC
LIMIT 5;Here's the breakdown of the most demanded skills for data analysts in 2023
-
SQL and Excel remain fundamental, emphasizing the need for strong foundational skills in data processing and spreadsheet manipulation.
-
Programming and Visualization Tools like Python, Tableau, and Power BI are essential, pointing towards the increasing importance of technical skills in data storytelling and decision support.
| 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
This query explored the relationship between specific skills and higher-than-average salaries. It was an insightful exercise in understanding how skills correlate with compensation.
SELECT
skills,
TO_CHAR(ROUND(AVG(salary_year_avg), 0), 'FM$999,999,999') AS avg_yearly_salary
FROM job_postings_fact
INNER JOIN skills_job_dim ON job_postings_fact.job_id = skills_job_dim.job_id
INNER JOIN skills_dim ON skills_job_dim.skill_id = skills_dim.skill_id
WHERE
job_title_short = 'Data Analyst'
AND salary_year_avg IS NOT NULL
AND job_work_from_home IS TRUE
GROUP BY
skills
ORDER BY
ROUND(AVG(salary_year_avg), 0) DESC
LIMIT 25;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 development and deployment tools (GitLab, Kubernetes, Airflow) indicates a lucrative crossover between data analysis and engineering, with a premium on skills that facilitate automation and efficient data pipeline management.
-
Cloud Computing Expertise: Familiarity with cloud and data engineering tools (Elasticsearch, Databricks, GCP) underscores the growing importance of cloud-based analytics environments, suggesting that cloud proficiency significantly boosts earning potential in data analytics.
| Skills | Average Yearly 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 yearly salary for the top 10 paying skills for data analysts
Combining insights from previous queries, I identified the skills that are both in high demand and associated with above-average salaries, providing a kind-of roadmap for aspiring data analysts.
SELECT
skills_job_dim.skill_id,
skills_dim.skills,
COUNT(skills_job_dim.job_id) AS demand_count,
TO_CHAR(ROUND(AVG(job_postings_fact.salary_year_avg), 2), 'FM$999,999,999') AS avg_salary
FROM job_postings_fact
INNER JOIN skills_job_dim ON job_postings_fact.job_id = skills_job_dim.job_id
INNER JOIN skills_dim ON skills_job_dim.skill_id = skills_dim.skill_id
WHERE
job_title_short = 'Data Analyst'
AND salary_year_avg IS NOT NULL
AND job_work_from_home IS TRUE
GROUP BY
skills_job_dim.skill_id,
skills_dim.skills
HAVING
COUNT(skills_job_dim.job_id) > 10
ORDER BY
ROUND(AVG(salary_year_avg)) DESC,
demand_count DESC
LIMIT 25;| Skill ID | Skills | Demand Count | Average Yearly 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
Here's a breakdown of the most optimal skills for Data Analysts in 2023:
-
High-Demand Programming Languages: Python and R stand out for their high demand, with demand counts of 236 and 148 respectively. Despite their high demand, their average salaries are around $101,397 for Python and $100,499 for R, indicating that proficiency in these languages is highly valued but also widely available.
-
Cloud Tools and Technologies: Skills in specialized technologies such as Snowflake, Azure, AWS, and BigQuery show significant demand with relatively high average salaries, pointing towards the growing importance of cloud platforms and big data technologies in data analysis.
-
Business Intelligence and Visualization Tools: Tableau and Looker, with demand counts of 230 and 49 respectively, and average salaries around $99,288 and $103,795, highlight the critical role of data visualization and business intelligence in deriving actionable insights from data.
-
Database Technologies: The demand for skills in traditional and NoSQL databases (Oracle, SQL Server, NoSQL) with average salaries ranging from $97,786 to $104,534, reflects the enduring need for data storage, retrieval, and management expertise.
Throughout this journey, I've strengthened my SQL skills and gained valuable experience:
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🧩 Complex Query Crafting: Improved my ability to write advanced SQL queries, including combining tables and using WITH clauses for temporary tables.
-
📊 Data Aggregation: Gained a better understanding of GROUP BY and how to use aggregate functions like COUNT() and AVG() to summarize data effectively.
-
💡 Analytical Problem-SOlving: Developed my skills in turning questions into actionable SQL queries, helping to uncover insights from data.
From the analysis, several general insights emerged:
-
Top-Paying Data Analyst Jobs: The highest-paying jobs for data analysts that allow remote work offer a wide range of salaries, the highest at $650,000!
-
Skills for Top-Paying Jobs: High-paying data analyst jobs require advanced proficiency in SQL, suggesting it’s a critical skill for earning a top salary.
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Most In-Demand Skills: SQL is also the most demanded skill in the data analyst job market, thus making it essential for job seekers.
-
Skills with Higher Salaries: Specialized skills, such as SVN and Solidity, are associated with the highest average salaries, indicating a premium on niche expertise.
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Optimal Skills for Job Market Value: SQL leads in demand and offers for a high average salary, positioning it as one of the most optimal skills for data analysts to learn to maximize their market value.
Through this project, I gained valuable insights into the data analyst job market. It’s clear that mastering specific skills like SQL and data visualization tools can significantly enhance career prospects.
This project also reinforced the importance of continuous learning and practicing skills to stay competitive in a rapidly evolving industry.
If you’re starting your journey in SQL, I highly recommend Luke Barousse’s SQL course—it’s beginner-friendly and packed with practical applications.
