The following table provides summary statistics for permanent job vacancies advertised in Glenrothes with a requirement for Power BI skills. Included is a benchmarking guide to the salaries offered in vacancies that have cited Power BI over the 6 months to 29 April 2024 with a comparison to the same period in the previous 2 years.
6 months to 29 Apr 2024
Same period 2023
Same period 2022
Rank
2
-
-
Rank change year-on-year
-
-
-
Permanent jobs citing Power BI
7
0
0
As % of all permanent jobs advertised in Glenrothes
Power BI is in the Databases and Business Intelligence category. The following table is for comparison with the above and provides summary statistics for all permanent job vacancies advertised in Glenrothes with a requirement for database or business intelligence skills.
Permanent vacancies with a requirement for database or business intelligence skills
7
2
1
As % of all permanent jobs advertised in Glenrothes
70.00%
40.00%
25.00%
Number of salaries quoted
7
2
1
10th Percentile
-
-
-
25th Percentile
£35,700
£46,250
-
Median annual salary (50th Percentile)
£43,200
£47,500
£50,000
Median % change year-on-year
-9.05%
-5.00%
-
75th Percentile
£45,600
£48,750
-
90th Percentile
-
-
-
Fife median annual salary
£40,000
£47,500
£50,000
% change year-on-year
-15.79%
-5.00%
-9.09%
Power BI Job Vacancy Trend in Glenrothes
Job postings citing Power BI as a proportion of all IT jobs advertised in Glenrothes.
Power BI Salary Trend in Glenrothes
3-month moving average salary quoted in jobs citing Power BI in Glenrothes.
Power BI Top 22 Co-occurring Skills and Capabilities in Glenrothes
For the 6 months to 29 April 2024, job vacancies citing Power BI also mentioned the following skills and capabilities in order of popularity.
The figures indicate the absolute number co-occurrences and as a proportion of all permanent job ads across the Glenrothes region with a requirement for Power BI.
Power BI Co-occurring Skills and Capabilities in Glenrothes by Category
The follow tables expand on the table above by listing co-occurrences grouped by category.
The same employment type, locality and period is covered with up to 20 co-occurrences shown in each of the following categories:
