The table below provides summary statistics for permanent job vacancies advertised in Sunderland requiring AWS Lambda skills. It includes a benchmarking guide to the annual salaries offered in vacancies that cited AWS Lambda 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
15
16
-
Rank change year-on-year
+1
-
-
Permanent jobs citing AWS Lambda
1
24
0
As % of all permanent jobs advertised in Sunderland
AWS Lambda falls under the Cloud Services category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring cloud computing skills in Sunderland.
Permanent vacancies with a requirement for cloud computing skills
12
90
10
As % of all permanent jobs advertised in Sunderland
25.53%
57.32%
14.71%
Number of salaries quoted
11
78
9
10th Percentile
-
£43,875
£30,800
25th Percentile
£32,500
£52,500
£36,250
Median annual salary (50th Percentile)
£40,000
£60,000
£40,000
Median % change year-on-year
-33.33%
+50.00%
+9.59%
75th Percentile
£71,250
£73,250
£43,750
90th Percentile
£80,000
£82,500
£65,400
Tyne and Wear median annual salary
£55,000
£50,000
£55,000
% change year-on-year
+10.00%
-9.09%
+4.76%
AWS Lambda Job Vacancy Trend in Sunderland
Job postings citing AWS Lambda as a proportion of all IT jobs advertised in Sunderland.
AWS Lambda Salary Trend in Sunderland
3-month moving average salary quoted in jobs citing AWS Lambda in Sunderland.
AWS Lambda Top 23 Co-occurring Skills and Capabilities in Sunderland
For the 6 months to 3 May 2025, job vacancies citing AWS Lambda 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 AWS Lambda.
AWS Lambda 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:
