Data Cleansing (Data Cleaning, Data Scrubbing) Staffordshire> Stoke-on-Trent
The table below provides summary statistics and salary benchmarking for jobs advertised in Stoke-on-Trent requiring Data Cleansing skills. It covers permanent job vacancies from the 6 months leading up to 5 October 2025, with comparisons to the same periods in the previous two years.
Data Cleansing 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 Stoke-on-Trent.
Permanent vacancies with a requirement for process or methodology skills
112
181
126
As % of all permanent jobs advertised in Stoke-on-Trent
88.19%
83.41%
95.45%
Number of salaries quoted
39
135
112
10th Percentile
£27,794
£24,000
£23,050
25th Percentile
£28,000
£31,250
£28,125
Median annual salary (50th Percentile)
£35,000
£40,000
£38,750
Median % change year-on-year
-12.50%
+3.23%
-3.13%
75th Percentile
£44,125
£55,000
£58,750
90th Percentile
£66,750
£65,000
£71,125
Staffordshire median annual salary
£42,500
£45,000
£42,500
% change year-on-year
-5.56%
+5.88%
-5.56%
Data Cleansing Job Vacancy Trend in Stoke-on-Trent
Historical trend showing the proportion of permanent IT job postings citing Data Cleansing relative to all permanent IT jobs advertised in Stoke-on-Trent.
Data Cleansing Salary Trend in Stoke-on-Trent
Salary distribution trend for jobs in Stoke-on-Trent citing Data Cleansing.
Data Cleansing Top 13 Co-Occurring Skills & Capabilities in Stoke-on-Trent
For the 6 months to 5 October 2025, job vacancies citing Data Cleansing also mentioned the following skills and capabilities in order of popularity.
The figures indicate the absolute number of co-occurrences and as a proportion of all permanent job ads across the Stoke-on-Trent region with a requirement for Data Cleansing.
Data Cleansing Co-Occurring Skills & Capabilities in Stoke-on-Trent by Category
The following tables expand on the one above by listing co-occurrences grouped by category. They cover the same employment type, locality and period, with up to 20 co-occurrences shown in each category:
