Data & Analytics Jobs
Jobs, Career & Information
Looking for a job in Data & Analytics in Belgium as a Data Analyst, BI Analyst or Data Scientist? Explore our current vacancies and learn more about roles, tools, specialisations and career opportunities.
Data & Analytics: at a glance
The role focuses on:
- Analysing datasets
- Building reports and dashboards
- Identifying trends and patterns
- Supporting business decision-making
Examples of jobs in data & analytics
What does a role in Data & Analytics involve?
The exact responsibilities depend on the role, but typically include:
- Collecting and structuring data
- Analysing datasets and trends
- Developing dashboards and reports
- Translating data into actionable business insights
- Optimising data processes
- Collaborating with business, IT and management teams
What are the roles and job titles within Data & Analytics?
Data Analysis & Reporting
- Data Analyst
- Reporting Analyst
- BI Analyst
- Insights Analyst
Business & Analytics
- Business Analyst with a data focus
- Analytics Consultant
- Data Specialist
Business Intelligence & Dashboarding
- BI Developer
- BI Consultant
- Reporting Specialist
Focus on:
- Dashboards
- Data visualisation
- Management reporting
Data Engineering, Architecture & Management
- Data Engineer
- Data Architect
- Data Manager
Focus on:
- Data pipelines
- Data structures
- Data governance
Advanced Analytics & Modelling
- Data Scientist
- Quantitative Analyst
- Machine Learning Specialist
Focus on:
- Predictive models
- Statistical analysis
- AI applications
Organisations often use different job titles for similar roles. It is therefore important to look beyond the job title and focus primarily on the actual responsibilities and scope of the role.
Tools and technologies used in Data Analysis
Data professionals work with a variety of tools and technologies, depending on their role.
Commonly used tools include:
- SQL for databases and queries
- Python or R for analysis and modelling
- Power BI and Tableau for data visualisation
- Excel for basic analysis and reporting
- ETL tools and data platforms for data processing
Depending on the role, the focus may be more on:
- Analysis for Data Analysts
- Visualisation for BI professionals
- Modelling for Data Scientists
- Infrastructure for Data Engineers
The tools you need therefore depend largely on the role. A BI professional, for example, will typically work more with SQL and Power BI, while Python or R becomes more important in data science and advanced analytics.
Specialisations within Data & Analytics
Within banks, insurers and other financial institutions, Data & Analytics professionals work across a wide range of business areas.
Risk & Finance Analytics
- Analysis of credit, market and operational risks
- Supporting risk management
- Financial analysis and forecasting
Commercial & Customer Analytics
- Customer segmentation
- Analysis of customer behaviour and needs
- Supporting marketing and sales
Regulatory & Reporting Data
- Data for compliance and regulatory reporting
- Supporting Solvency II, Basel and IFRS requirements
- Data quality and governance
Operational Analytics
- Analysis of internal processes
- Efficiency and process optimisation
- Cost controlling and performance analysis
What makes Data & Analytics in Banking and Insurance unique?
Data & Analytics roles within banks and insurance companies are characterised by the combination of large volumes of data, strict regulatory requirements and high standards for data quality and governance.
Key characteristics include:
- Large volumes of data
- A highly regulated environment
- High standards for data quality
- Close collaboration with risk, finance and compliance teams
Data is used not only for analysis, but also for:
- Regulatory reporting
- Risk management
- Strategic decision-making
- Operational and commercial optimisation
What profiles are employers looking for?
Typical backgrounds include:
- A Bachelor’s or Master’s degree in areas such as Economics, Statistics, Mathematics, Computer Science, Data Science or a related field
- Strong analytical skills
- An interest in both data and business
- Knowledge of relevant tools, depending on the role
Employers also place significant importance on:
- Strong communication skills
- The ability to translate data into actionable insights
- Accuracy and attention to data quality
- The ability to collaborate effectively with business teams and other stakeholders
Job market for Data & Analytics professionals in Belgium
Data & Analytics continues to be a rapidly growing field within the financial sector.
There is strong demand for:
- Data Analysts and BI professionals
- Business Analysts with a data focus
- Data Engineers and Data Architects
- Data Scientists and specialised Analytics professionals
- Candidates with knowledge of the financial sector
Opportunities can be found at:
- Banks and financial institutions
- Insurance companies
- Asset managers
- Fintech and payment companies
- Consulting firms
Within these organisations, data plays an increasingly important role in areas such as reporting, risk management, customer insights, process optimisation and strategic decision-making. This creates opportunities for both technical data professionals and professionals who combine data analysis with a strong understanding of the financial sector.
Career progression within Data & Analytics
A career in Data & Analytics offers opportunities to progress both as a specialist and into management roles.
Possible career paths include:
- Senior Data Analyst
- Data Scientist or Specialist
- Data Lead
- Analytics Manager
- Head of Data / Analytics
You can also move into other areas, such as:
- Risk Management
- Finance
- Strategy
- Consulting
Career progression does not necessarily mean moving into management. You can also continue to develop your expertise and progress as a specialist.
Working in Data & Analytics through Azuro
At Azuro, we help Data & Analytics professionals find roles within banking, insurance and the broader financial sector.
We look beyond your technical skills and also consider the environment in which you want to apply them, for example within:
- Risk
- Finance
- Compliance
- Reporting
- Commercial Analytics
We combine:
- Knowledge of Data & Analytics roles within banking and insurance
- An understanding of how data interacts with finance, risk and compliance
- Access to a strong network of employers
- Personal guidance and honest feedback
- A discreet approach
We help you take a well-considered next step in your career.
Ready for the next step?
Explore our vacancies and apply, or send us your CV so we can contact you when suitable job opportunities arise.
FAQ - Data & Analytics jobs
How much does a Data Analyst earn in Belgium?
The salary of a Data Analyst in Belgium depends on experience, specialisation, sector and technical expertise.
Indicative gross monthly salaries:
- Junior: €2,800–€3,600 per month
- Mid-level: €3,600–€5,000 per month
- Senior: €5,000–€6,500+ per month
Salaries can be higher for professionals with specialised technical expertise, as well as for Data Scientists, Data Engineers and those in senior or management positions.
In addition to the base salary, remuneration packages often include fringe benefits such as a performance-related bonus, group insurance, hospitalisation insurance, net allowances and a company car or mobility budget.
The exact package varies depending on the employer, role and level of seniority.
What Is the difference between a Data Analyst and a Data Scientist?
A Data Analyst primarily analyses existing data to identify trends, create reports and dashboards, and translate data into actionable business insights.
A Data Scientist typically works with more advanced statistical techniques, predictive models and machine learning to identify patterns and make predictions based on large or complex datasets.
In practice, the distinction is not always clear-cut, and responsibilities can overlap depending on the organisation.
Do you need programming skills for a job in Data & Analytics?
Not for every role.
For Data Science and more technical Analytics roles, knowledge of Python or R is often important. For Data Analysts and BI professionals, skills in SQL, Excel, Power BI or Tableau are typically more relevant.
The technical skills required therefore depend strongly on the role. Business understanding, analytical thinking and the ability to communicate insights effectively are equally important.
Is there a high demand for Data & Analytics professionals?
Yes. Data & Analytics remains an important growth area, particularly within banks, insurance companies, fintechs and other financial institutions.
There is strong demand for Data Analysts, BI professionals, Data Engineers, Data Scientists and Business Analysts with a strong data focus.
Employers particularly value candidates who can combine technical skills with business insight and translate data into actionable insights that support decision-making.
What qualifications do you need for a job in Data & Analytics?
Many Data & Analytics professionals have a Bachelor’s or Master’s degree in Economics, Computer Science, Data Science, Statistics, Mathematics or a related field.
However, a specific degree in Data Science or Analytics is not required for every role. Employers also value relevant technical skills, analytical ability, hands-on experience with data and the ability to translate analysis into actionable business insights.
Can you progress your career in Data & Analytics?
Yes. You can progress both as a specialist and into management roles.
Possible career paths include:
- Senior Data Analyst
- Data Scientist or Specialist
- Data Lead
- Analytics Manager
- Head of Data / Analytics
A career in data can also open up opportunities in related areas such as Risk Management, Finance, Strategy or Consulting.
Do you need experience in Finance to work in Data & Analytics?
Not always. For many Data & Analytics roles, you can enter the field with strong analytical or technical skills without previous experience in the financial sector.
Within banks and insurance companies, however, knowledge of finance, risk, compliance or regulatory reporting is a clear advantage. Particularly for more specialised roles, sector knowledge helps you interpret data correctly and translate analysis into relevant business decisions.