The following table is for comparison with the above and includes summary statistics for all contract IT job vacancies advertised in Leeds. Most job vacancies include a discernible job title that can be normalized. As such, the figures in the second row provide an indication of the number of contract jobs in our overall sample.
Contract vacancies in Leeds with a recognized job title
730
1,290
1,532
% of contract IT jobs with a recognized job title
92.17%
98.02%
97.39%
Number of daily rates quoted
455
942
1,126
10th Percentile
£300
£355
£275
25th Percentile
£413
£450
£413
Median daily rate (50th Percentile)
£500
£538
£500
Median % change year-on-year
-6.98%
+7.50%
+8.11%
75th Percentile
£588
£619
£575
90th Percentile
£675
£700
£650
West Yorkshire median daily rate
£500
£525
£500
% change year-on-year
-4.76%
+5.00%
+11.11%
Number of hourly rates quoted
13
11
22
10th Percentile
£11.24
£12.00
£15.50
25th Percentile
£11.75
£16.50
£18.25
Median hourly rate
£12.53
£62.50
£22.40
Median % change year-on-year
-79.95%
+179.02%
+3.04%
75th Percentile
£15.25
£70.00
£26.50
90th Percentile
£17.67
-
£28.60
West Yorkshire median hourly rate
£14.34
£32.50
£16.85
% change year-on-year
-55.89%
+92.88%
-22.49%
Python Data Engineer Job Vacancy Trend in Leeds
Job postings that featured Python Data Engineer in the job title as a proportion of all IT jobs advertised in Leeds.
Python Data Engineer Contractor Daily Rate Trend in Leeds
3-month moving average daily rate quoted in jobs citing Python Data Engineer in Leeds.
Python Data Engineer Skill Set Top 21 Co-occurring Skills and Capabilities in Leeds
For the 6 months to 2 May 2024, Python Data Engineer contract job roles required the following skills and capabilities in order of popularity.
The figures indicate the absolute number co-occurrences and as a proportion of all contract job ads across the Leeds region featuring Python Data Engineer in the job title.
Python Data Engineer Skill Set Co-occurring Skills and Capabilities in Leeds 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:
