The table below provides summary statistics for permanent job vacancies advertised in Cambridge requiring Power Query skills. It includes a benchmarking guide to the annual salaries offered in vacancies that cited Power Query over the 6 months leading up to 30 May 2025, comparing them to the same period in the previous two years.
6 months to 30 May 2025
Same period 2024
Same period 2023
Rank
42
-
88
Rank change year-on-year
-
-
-
Permanent jobs citing Power Query
2
0
3
As % of all permanent jobs advertised in Cambridge
Power Query 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 Cambridge.
Permanent vacancies with a requirement for database or business intelligence skills
43
107
104
As % of all permanent jobs advertised in Cambridge
17.06%
10.42%
11.50%
Number of salaries quoted
33
83
59
10th Percentile
-
£31,250
£36,250
25th Percentile
£26,250
£41,718
£42,500
Median annual salary (50th Percentile)
£27,500
£60,000
£50,000
Median % change year-on-year
-54.17%
+20.00%
-11.11%
75th Percentile
£38,890
£77,500
£67,500
90th Percentile
£70,750
£92,500
£92,500
Cambridgeshire median annual salary
£45,000
£55,000
£55,000
% change year-on-year
-18.18%
-
+10.00%
Power Query Job Vacancy Trend in Cambridge
Job postings citing Power Query as a proportion of all IT jobs advertised in Cambridge.
Power Query Salary Trend in Cambridge
3-month moving average salary quoted in jobs citing Power Query in Cambridge.
Power Query Top 11 Co-occurring Skills and Capabilities in Cambridge
For the 6 months to 30 May 2025, job vacancies citing Power Query 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 Cambridge region with a requirement for Power Query.
Power Query Co-occurring Skills and Capabilities in Cambridge 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:
