SQL Optimisation Job Trends in Preston

SQL Optimisation
Lancashire > Preston

The table below provides summary statistics and salary benchmarking for jobs advertised in Preston citing SQL Optimisation skills. It covers permanent job vacancies from the 6 months leading up to 24 October 2026, with comparisons to the same periods in the previous two years.

6 months to
24 Oct 2026
Same period 2025 Same period 2024
Rank 34 - -
Rank change year-on-year - - -
Permanent jobs citing SQL Optimisation 2 0 0
As % of all permanent jobs in Preston 0.56% - -
As % of the Processes & Methodologies category 0.84% - -
Number of salaries quoted 0 0 0
Median annual salary (50th Percentile) - - -
Lancashire median annual salary - - -

All Process & Methodology Skills
Preston

SQL Optimisation falls under the Processes and Methodologies category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies citing process or methodology skills in Preston.

6 months to
24 Oct 2026
Same period 2025 Same period 2024
Permanent vacancies citing process or methodology skills 239 36 139
As % of all permanent jobs advertised in Preston 66.57% 70.59% 98.58%
Number of salaries quoted 185 29 103
10th Percentile £33,046 £30,000 £32,600
25th Percentile £40,000 £41,250 £40,625
Median annual salary (50th Percentile) £50,000 £47,683 £50,500
Median % change year-on-year +4.86% -5.58% +8.54%
75th Percentile £70,000 £57,000 £65,000
90th Percentile £78,000 £73,400 £72,400
Lancashire median annual salary £47,160 £45,000 £50,055
% change year-on-year +4.80% -10.10% +0.11%

SQL Optimisation Job Vacancy Trend in Preston

Historical trend showing the proportion of permanent IT job postings citing SQL Optimisation relative to all permanent IT jobs advertised in Preston.

SQL Optimisation job vacancy trend in Preston

SQL Optimisation Co-Occurring Skills & Capabilities in Preston by Category

The table below expands on the one above by listing co-occurrences one category at a time. It covers the same employment type, locality and period, with up to 20 co-occurrences in each category.