The table below provides summary statistics for permanent job vacancies advertised in Sunderland requiring Logical Data Model skills. It includes a benchmarking guide to the annual salaries offered in vacancies that cited Logical Data Model over the 6 months leading up to 31 May 2025, comparing them to the same period in the previous two years.
6 months to 31 May 2025
Same period 2024
Same period 2023
Rank
18
-
-
Rank change year-on-year
-
-
-
Permanent jobs citing Logical Data Model
1
0
0
As % of all permanent jobs advertised in Sunderland
Logical Data Model falls under the Processes and Methodologies category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring process or methodology skills in Sunderland.
Permanent vacancies with a requirement for process or methodology skills
53
157
72
As % of all permanent jobs advertised in Sunderland
94.64%
91.28%
97.30%
Number of salaries quoted
25
137
29
10th Percentile
-
£35,000
£30,500
25th Percentile
£25,087
£40,177
£36,750
Median annual salary (50th Percentile)
£40,000
£55,000
£55,000
Median % change year-on-year
-27.27%
-
+29.41%
75th Percentile
£51,500
£67,500
£67,500
90th Percentile
£65,000
£77,200
£72,100
Tyne and Wear median annual salary
£45,000
£47,500
£52,500
% change year-on-year
-5.26%
-9.52%
+10.53%
Logical Data Model Job Vacancy Trend in Sunderland
Job postings citing Logical Data Model as a proportion of all IT jobs advertised in Sunderland.
Logical Data Model Top 10 Co-occurring Skills and Capabilities in Sunderland
For the 6 months to 31 May 2025, job vacancies citing Logical Data Model 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 Sunderland region with a requirement for Logical Data Model.
Logical Data Model Co-occurring Skills and Capabilities in Sunderland 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:
