Microsoft Power BI
Surrey > Walton-on-Thames
The table below provides summary statistics and salary benchmarking for jobs advertised in Walton-on-Thames requiring Power BI skills. It covers permanent job vacancies from the 6 months leading up to 14 December 2025, with comparisons to the same periods in the previous two years.
| 6 months to 14 Dec 2025 |
Same period 2024 | Same period 2023 | |
|---|---|---|---|
| Rank | 3 | - | - |
| Rank change year-on-year | - | - | - |
| Permanent jobs citing Power BI | 2 | 0 | 0 |
| As % of all permanent jobs in Walton-on-Thames | 18.18% | - | - |
| As % of the Database & Business Intelligence category | 100.00% | - | - |
| Number of salaries quoted | 0 | 0 | 0 |
| Median annual salary (50th Percentile) | - | - | - |
| Surrey median annual salary | £52,500 | £56,000 | £47,500 |
| % change year-on-year | -6.25% | +17.89% | -9.52% |
All Database and Business Intelligence Skills
Walton-on-Thames
Power BI falls under the Databases and Business Intelligence category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring database or business intelligence skills in Walton-on-Thames.
| Permanent vacancies with a requirement for database or business intelligence skills | 2 | 0 | 0 |
| As % of all permanent jobs advertised in Walton-on-Thames | 18.18% | - | - |
| Number of salaries quoted | 0 | 0 | 0 |
| Median annual salary (50th Percentile) | - | - | - |
| Surrey median annual salary | £60,000 | £52,500 | £55,000 |
| % change year-on-year | +14.29% | -4.55% | +4.76% |
Power BI
Job Vacancy Trend in Walton-on-Thames
Historical trend showing the proportion of permanent IT job postings citing Power BI relative to all permanent IT jobs advertised in Walton-on-Thames.
Power BI
Salary Trend in Walton-on-Thames
Salary distribution trend for jobs in Walton-on-Thames citing Power BI.
Power BI
Co-Occurring Skills & Capabilities in Walton-on-Thames by Category
The following tables expand on the one above by listing co-occurrences grouped by category. They cover the same employment type, locality and period, with up to 20 co-occurrences shown in each category: