🌍 Eager to dive into the world of data science jobs in the European Union (EU)?
Discover the highest-paying roles for data analysts and business analysts, and uncover the essential skills you need to excel in these positions.
🔗 Access the SQL queries that powered these insights here: project_sql folder
Starting out in the field of data science, I decided to explore the job market to identify the most valuable skills to learn.
- What are the top-paying data analyst jobs?
- What skills 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?
- SQL: To efficiently extract and analyze the necessary data.
- PostgreSQL: Ideal for managing and processing job market data.
- Visual Studio Code: Used for writing and executing SQL queries.
- Git & GitHub: Essential for version control and collaboration.
- Excel: Utilized for creating clear and insightful data visualizations.
I broke down each key question into specific queries:
I identified the top 10 highest-paying roles in the EU for data analysts and business analysts by filtering data based on job title, average yearly salary, and location.
SELECT
job_id,
job_title,
job_title_short,
name AS company_name,
job_location,
salary_year_avg,
job_schedule_type,
job_posted_date
FROM
job_postings_fact
LEFT JOIN company_dim
ON job_postings_fact.company_id = company_dim.company_id
WHERE
job_title_short IN ('Data Analyst','Business Analyst') AND
job_location LIKE ANY (ARRAY[
'%Austria%', '%Belgium%', '%Bulgaria%', '%Croatia%', '%Cyprus%',
'%Czech Republic%', '%Denmark%', '%Estonia%', '%Finland%', '%France%',
'%Germany%', '%Greece%', '%Hungary%', '%Ireland%', '%Italy%',
'%Latvia%', '%Lithuania%', '%Luxembourg%', '%Malta%', '%Netherlands%',
'%Poland%', '%Portugal%', '%Romania%', '%Slovakia%', '%Slovenia%',
'%Spain%', '%Sweden%'
]) AND
salary_year_avg IS NOT NULL
ORDER BY
salary_year_avg DESC
LIMIT 10;
Bar graph visualising the salary for the top 10 salaries for data analysts and business analysts
For the top-paying jobs identified, I analyzed the specific skills required for each role.
WITH top_paying_jobs AS (
SELECT
job_id,
job_title,
salary_year_avg,
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 IN ('Data Analyst','Business Analyst') AND
job_location LIKE ANY (ARRAY[
'%Austria%', '%Belgium%', '%Bulgaria%', '%Croatia%', '%Cyprus%',
'%Czech Republic%', '%Denmark%', '%Estonia%', '%Finland%', '%France%',
'%Germany%', '%Greece%', '%Hungary%', '%Ireland%', '%Italy%',
'%Latvia%', '%Lithuania%', '%Luxembourg%', '%Malta%', '%Netherlands%',
'%Poland%', '%Portugal%', '%Romania%', '%Slovakia%', '%Slovenia%',
'%Spain%', '%Sweden%'
]) AND
salary_year_avg IS NOT NULL
ORDER BY
salary_year_avg DESC
LIMIT 10
)
SELECT
top_paying_jobs.*,
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
salary_year_avg DESC;
Bar graph visualising the skill count for the top paying roles for data analysts and business analysts
I aggregated the skills required for these roles across the EU and identified the top 5 most in-demand skills.
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 IN ('Data Analyst','Business Analyst') AND
job_location LIKE ANY (ARRAY[
'%Austria%', '%Belgium%', '%Bulgaria%', '%Croatia%', '%Cyprus%',
'%Czech Republic%', '%Denmark%', '%Estonia%', '%Finland%', '%France%',
'%Germany%', '%Greece%', '%Hungary%', '%Ireland%', '%Italy%',
'%Latvia%', '%Lithuania%', '%Luxembourg%', '%Malta%', '%Netherlands%',
'%Poland%', '%Portugal%', '%Romania%', '%Slovakia%', '%Slovenia%',
'%Spain%', '%Sweden%'
])
GROUP BY
skills
ORDER BY
demand_count DESC
LIMIT 5;| Skills | Demand Count |
|---|---|
| SQL | 28,550 |
| Python | 18,920 |
| Excel | 18,543 |
| Power BI | 14,690 |
| Tableau | 12,710 |
I filtered data from all relevant job postings in the EU to identify the top 25 highest-paying skills.
SELECT
skills,
ROUND(AVG (salary_year_avg)) 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
salary_year_avg IS NOT NULL AND
job_title_short IN ('Data Analyst','Business Analyst') AND
job_location LIKE ANY (ARRAY[
'%Austria%', '%Belgium%', '%Bulgaria%', '%Croatia%', '%Cyprus%',
'%Czech Republic%', '%Denmark%', '%Estonia%', '%Finland%', '%France%',
'%Germany%', '%Greece%', '%Hungary%', '%Ireland%', '%Italy%',
'%Latvia%', '%Lithuania%', '%Luxembourg%', '%Malta%', '%Netherlands%',
'%Poland%', '%Portugal%', '%Romania%', '%Slovakia%', '%Slovenia%',
'%Spain%', '%Sweden%'
])
GROUP BY
skills
ORDER BY
avg_salary DESC
LIMIT 10;| Skills | Average Salary ($) |
|---|---|
| Mongo | 165,000 |
| Unify | 163,782 |
| Smartsheet | 155,000 |
| C | 143,200 |
| Spring | 140,905 |
| NoSQL | 135,419 |
| Flask | 126,040 |
| Slack | 126,000 |
| Linux | 123,901 |
| Terraform | 120,067 |
I combined the results from previous analyses to determine which skills are both highly demanded and command higher salaries, ensuring the recommended skills offer the best return on investment.
WITH skills_demand AS (
-- Identifies skills in high demand for Data Analyst and Business Analyst roles
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 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
salary_year_avg IS NOT NULL
AND job_title_short IN ('Data Analyst', 'Business Analyst')
AND job_location LIKE ANY (ARRAY[
'%Austria%', '%Belgium%', '%Bulgaria%', '%Croatia%', '%Cyprus%',
'%Czech Republic%', '%Denmark%', '%Estonia%', '%Finland%', '%France%',
'%Germany%', '%Greece%', '%Hungary%', '%Ireland%', '%Italy%',
'%Latvia%', '%Lithuania%', '%Luxembourg%', '%Malta%', '%Netherlands%',
'%Poland%', '%Portugal%', '%Romania%', '%Slovakia%', '%Slovenia%',
'%Spain%', '%Sweden%'
])
GROUP BY
skills_dim.skill_id, skills_dim.skills
),
average_salary AS (
-- Skills with high average salaries for Data Analyst and Business Analyst roles
SELECT
skills_job_dim.skill_id,
ROUND(AVG(job_postings_fact.salary_year_avg)) AS avg_salary
FROM
job_postings_fact
INNER JOIN skills_job_dim
ON job_postings_fact.job_id = skills_job_dim.job_id
WHERE
salary_year_avg IS NOT NULL
AND job_title_short IN ('Data Analyst', 'Business Analyst')
AND job_location LIKE ANY (ARRAY[
'%Austria%', '%Belgium%', '%Bulgaria%', '%Croatia%', '%Cyprus%',
'%Czech Republic%', '%Denmark%', '%Estonia%', '%Finland%', '%France%',
'%Germany%', '%Greece%', '%Hungary%', '%Ireland%', '%Italy%',
'%Latvia%', '%Lithuania%', '%Luxembourg%', '%Malta%', '%Netherlands%',
'%Poland%', '%Portugal%', '%Romania%', '%Slovakia%', '%Slovenia%',
'%Spain%', '%Sweden%'
])
GROUP BY
skills_job_dim.skill_id
)
-- Return high demand and high salaries for top 10 skills
SELECT
skills_demand.skill_id,
skills_demand.skills,
skills_demand.demand_count,
average_salary.avg_salary
FROM
skills_demand
INNER JOIN average_salary
ON skills_demand.skill_id = average_salary.skill_id
WHERE
demand_count > 10
ORDER BY
demand_count DESC,
avg_salary DESC
LIMIT 10;| Skill ID | Skills | Demand Count | Average Salary ($) |
|---|---|---|---|
| 0 | SQL | 219 | 92,893 |
| 1 | Python | 156 | 94,176 |
| 182 | Tableau | 118 | 88,964 |
| 181 | Excel | 98 | 77,291 |
| 183 | Power BI | 76 | 87,602 |
| 5 | R | 57 | 89,406 |
| 74 | Azure | 49 | 109,609 |
| 92 | Spark | 43 | 109,633 |
| 185 | Looker | 34 | 98,792 |
| 189 | SAP | 34 | 89,855 |
The highest-paying roles in the EU for data analysts and business analysts offer salaries up to $200,000. Many of these positions are categorized under the title of Research Engineer.
To secure these high-paying roles, advanced proficiency in SQL, Python, and Spark is essential. These skills are crucial for excelling in top-tier positions.
SQL and Python are among the most sought-after skills in the data analyst and business analyst job markets. Additionally, skills in Excel and data visualization tools such as Power BI and Tableau are also highly demanded.
Top-paying skills often involve specialized software programs, such as MongoDB and Unify. These niche expertise areas are linked to the highest average salaries, indicating their premium value in the job market.
SQL and Python not only top the list in terms of demand but also offer competitive salaries. Mastering these skills, along with Excel and advanced visualization tools, ranks candidates favourably in the job market, increasing their potential for high earnings.
This project has improved my data analytics skills, enhancing both my technical proficiency and analytical capabilities:
👨🏻💻 Advanced SQL Techniques: Expanded my expertise with advanced SQL features, such as JOINs and subqueries, and leveraged powerful tools like CTEs to handle intricate data scenarios with ease.
✨ Problem Solving: Tackled various challenges, from troubleshooting query errors to optimizing performance. Each problem sharpened my ability to analyze and interpret results more effectively.
📊 Data Aggregation: Mastered the use of aggregation techniques, including GROUP BY and functions like COUNT and AVG, to summarize and extract meaningful insights from complex datasets.