The table below provides summary statistics for permanent job vacancies advertised in Maidstone requiring MongoDB skills. It includes a benchmarking guide to the annual salaries offered in vacancies that cited MongoDB over the 6 months leading up to 3 May 2025, comparing them to the same period in the previous two years.
6 months to 3 May 2025
Same period 2024
Same period 2023
Rank
13
31
-
Rank change year-on-year
+18
-
-
Permanent jobs citing MongoDB
3
5
0
As % of all permanent jobs advertised in Maidstone
MongoDB 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 Maidstone.
Permanent vacancies with a requirement for database or business intelligence skills
14
25
8
As % of all permanent jobs advertised in Maidstone
21.88%
13.37%
2.61%
Number of salaries quoted
11
22
8
10th Percentile
£26,000
£36,250
£36,650
25th Percentile
-
£44,375
£44,000
Median annual salary (50th Percentile)
£30,000
£49,000
£46,750
Median % change year-on-year
-38.78%
+4.81%
-10.95%
75th Percentile
£53,250
£61,250
£63,125
90th Percentile
£75,000
£65,000
£80,000
Kent median annual salary
£42,500
£55,000
£52,500
% change year-on-year
-22.73%
+4.76%
+23.53%
MongoDB Job Vacancy Trend in Maidstone
Job postings citing MongoDB as a proportion of all IT jobs advertised in Maidstone.
MongoDB Salary Trend in Maidstone
3-month moving average salary quoted in jobs citing MongoDB in Maidstone.
MongoDB Top 10 Co-occurring Skills and Capabilities in Maidstone
For the 6 months to 3 May 2025, job vacancies citing MongoDB 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 Maidstone region with a requirement for MongoDB.
MongoDB Co-occurring Skills and Capabilities in Maidstone 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:
