The table below provides summary statistics for permanent job vacancies advertised in St Albans requiring Big Data skills. It includes a benchmarking guide to the annual salaries offered in vacancies that cited Big Data over the 6 months leading up to 8 May 2025, comparing them to the same period in the previous two years.
6 months to 8 May 2025
Same period 2024
Same period 2023
Rank
9
-
-
Rank change year-on-year
-
-
-
Permanent jobs citing Big Data
3
0
0
As % of all permanent jobs advertised in St Albans
Big Data 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 St Albans.
Permanent vacancies with a requirement for database or business intelligence skills
9
22
10
As % of all permanent jobs advertised in St Albans
21.95%
21.78%
8.13%
Number of salaries quoted
5
22
7
10th Percentile
£50,950
£53,250
£52,750
25th Percentile
£51,250
£60,000
£59,375
Median annual salary (50th Percentile)
£60,000
£85,000
£67,500
Median % change year-on-year
-29.41%
+25.93%
-11.48%
75th Percentile
£76,000
£115,000
£71,250
90th Percentile
£93,400
£118,375
£74,750
Hertfordshire median annual salary
£62,500
£50,000
£60,000
% change year-on-year
+25.00%
-16.67%
+4.35%
Big Data Job Vacancy Trend in St Albans
Job postings citing Big Data as a proportion of all IT jobs advertised in St Albans.
Big Data Salary Trend in St Albans
3-month moving average salary quoted in jobs citing Big Data in St Albans.
Big Data Top 17 Co-occurring Skills and Capabilities in St Albans
For the 6 months to 8 May 2025, job vacancies citing Big Data 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 St Albans region with a requirement for Big Data.
Big Data Co-occurring Skills and Capabilities in St Albans 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:
