Data Engineer
Ealing > Southall
As of 28 February 2026, there is not enough information available from job vacancies posted within the last 6 months to determine the median Data Engineer salary in Southall.
| 6 months to 28 Feb 2026 |
Same period 2025 | Same period 2024 | |
|---|---|---|---|
| Rank | 10 | - | - |
| Rank change year-on-year | - | - | - |
| Permanent jobs requiring a Data Engineer | 2 | 0 | 0 |
| As % of all permanent jobs in Southall | 6.90% | - | - |
| As % of the Job Titles category | 7.14% | - | - |
| Number of salaries quoted | 0 | 0 | 0 |
| Median annual salary (50th Percentile) | - | - | - |
| Ealing median annual salary | - | - | - |
All Permanent IT Job Roles
Southall
For comparison with the information above, the following table provides summary statistics for all permanent IT job vacancies in Southall. 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 permanent jobs in our overall sample.
| Permanent vacancies in Southall with a recognized job title | 28 | 1 | 2 |
| % of permanent jobs with a recognized job title | 96.55% | 100.00% | 100.00% |
| Number of salaries quoted | 4 | 0 | 2 |
| 10th Percentile | - | - | £41,375 |
| 25th Percentile | - | - | £43,438 |
| Median annual salary (50th Percentile) | £24,000 | - | £48,750 |
| 75th Percentile | - | - | £55,938 |
| 90th Percentile | - | - | £59,125 |
| Ealing median annual salary | £50,000 | £44,561 | £52,500 |
| % change year-on-year | +12.21% | -15.12% | +50.00% |
Data Engineer Skill Set
Top 30 Co-Occurring Skills & Capabilities in Southall
For the 6 months to 28 February 2026, Data Engineer job roles required 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 Southall region featuring Data Engineer in the job title.
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Data Engineer Skill Set
Co-Occurring Skills & Capabilities in Southall 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: