Data Professional Roles and Salaries: Comparison by Role and Job Level
Posted: Sun Jan 05, 2025 10:00 am
Below, what you will see in this article:
The Data Age and Its Countless Professional Opportunities
What is the role and salary of a Data Professional?
1. Data Analyst: Uncovering Valuable Insights
2. Data Scientist: Discovering Hidden Patterns and Building Predictive Models
3. Business Intelligence Analyst: Lighting the Strategic Path
4. Data Engineer: Building the Backstage Structures
How to Advance Your Career to Work in the Data Industry and Achieve Professional Success
What to Study to Become a Data Professional?
The Data Age and Its Countless Professional Opportunities
We live in an era where information is the most valuable asset, and companies across all industries are harnessing the power of data to make more informed decisions and drive growth. In this scenario, data careers have emerged as some of the most promising and in-demand careers in the market. In addition to exploring the distinct characteristics of each role, its essential skills, and the key tools required, this article will also provide an overview of the average salaries associated with each of these professions.
What are the Roles and Salaries of Data Professionals?
1. Data Analyst: Uncovering Valuable Insights
Data analysts are the numbers crunchers of the world. They have the ability to transform raw data into clear, actionable insights. Their main responsibilities include collecting, cleaning, and organizing data, applying statistical analysis, and creating impactful visualizations.
Essential Skills: Proficiency in programming languages such as SQL and malta email list Python, solid knowledge of statistics, effective communication skills to translate technical insights into understandable language.
Important Tools:
SQL
Python
Excel
Power BI
Tableau
Project developed: User Behavior Analysis on an E-Commerce Website
Collect browsing and transaction data from an e-commerce website.
Clean and organize data for analysis.
Perform exploratory analysis to identify user behavior patterns.
Create interactive visualizations to highlight most popular products, peak traffic times, etc.
Propose recommendations for website improvements based on the insights gained.
Average Salary for Data Analyst / Business Intelligence professionals by Job Level.
Below we are ranking the salary values that have the highest percentage by job level:
Junior: 45.8% have a salary between R$2k/month and R$4k/month
Full: 34% have a salary between R$4k/month and R$6k/month
Senior: 43% have a salary between R$8k/month and R$12k/month
(Source: State of Data 2022 )
2. Data Scientist: Discovering Hidden Patterns and Building Predictive Models
Data scientists go beyond descriptive analysis and into forecasting and modeling. They develop complex algorithms and machine learning models to identify patterns and trends in data in order to predict future events and make strategic decisions.
Essential Skills: Deep understanding of statistics and machine learning, advanced programming skills in Python or R, ability to handle large data sets and build robust predictive models.
The Data Age and Its Countless Professional Opportunities
What is the role and salary of a Data Professional?
1. Data Analyst: Uncovering Valuable Insights
2. Data Scientist: Discovering Hidden Patterns and Building Predictive Models
3. Business Intelligence Analyst: Lighting the Strategic Path
4. Data Engineer: Building the Backstage Structures
How to Advance Your Career to Work in the Data Industry and Achieve Professional Success
What to Study to Become a Data Professional?
The Data Age and Its Countless Professional Opportunities
We live in an era where information is the most valuable asset, and companies across all industries are harnessing the power of data to make more informed decisions and drive growth. In this scenario, data careers have emerged as some of the most promising and in-demand careers in the market. In addition to exploring the distinct characteristics of each role, its essential skills, and the key tools required, this article will also provide an overview of the average salaries associated with each of these professions.
What are the Roles and Salaries of Data Professionals?
1. Data Analyst: Uncovering Valuable Insights
Data analysts are the numbers crunchers of the world. They have the ability to transform raw data into clear, actionable insights. Their main responsibilities include collecting, cleaning, and organizing data, applying statistical analysis, and creating impactful visualizations.
Essential Skills: Proficiency in programming languages such as SQL and malta email list Python, solid knowledge of statistics, effective communication skills to translate technical insights into understandable language.
Important Tools:
SQL
Python
Excel
Power BI
Tableau
Project developed: User Behavior Analysis on an E-Commerce Website
Collect browsing and transaction data from an e-commerce website.
Clean and organize data for analysis.
Perform exploratory analysis to identify user behavior patterns.
Create interactive visualizations to highlight most popular products, peak traffic times, etc.
Propose recommendations for website improvements based on the insights gained.
Average Salary for Data Analyst / Business Intelligence professionals by Job Level.
Below we are ranking the salary values that have the highest percentage by job level:
Junior: 45.8% have a salary between R$2k/month and R$4k/month
Full: 34% have a salary between R$4k/month and R$6k/month
Senior: 43% have a salary between R$8k/month and R$12k/month
(Source: State of Data 2022 )
2. Data Scientist: Discovering Hidden Patterns and Building Predictive Models
Data scientists go beyond descriptive analysis and into forecasting and modeling. They develop complex algorithms and machine learning models to identify patterns and trends in data in order to predict future events and make strategic decisions.
Essential Skills: Deep understanding of statistics and machine learning, advanced programming skills in Python or R, ability to handle large data sets and build robust predictive models.