Snowflake Schema Job Trends in Kingston Upon Thames

Snowflake Schema
South London > Kingston Upon Thames

The table below provides summary statistics and salary benchmarking for jobs advertised in Kingston Upon Thames requiring Snowflake Schema skills. It covers permanent job vacancies from the 6 months leading up to 13 March 2026, with comparisons to the same periods in the previous two years.

6 months to
13 Mar 2026
Same period 2025 Same period 2024
Rank 32 - -
Rank change year-on-year - - -
Permanent jobs citing Snowflake Schema 2 0 0
As % of all permanent jobs in Kingston Upon Thames 1.08% - -
As % of the Database & Business Intelligence category 9.09% - -
Number of salaries quoted 0 0 0
Median annual salary (50th Percentile) - - -
South London median annual salary - - -

All Database & Business Intelligence Skills
Kingston Upon Thames

Snowflake Schema 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 Kingston Upon Thames.

Permanent vacancies with a requirement for database or business intelligence skills 22 24 10
As % of all permanent jobs advertised in Kingston Upon Thames 11.83% 17.02% 4.15%
Number of salaries quoted 6 3 10
10th Percentile £59,375 £52,850 £41,000
25th Percentile £77,500 £54,125 £46,375
Median annual salary (50th Percentile) £80,000 £57,500 £66,250
Median % change year-on-year +39.13% -13.21% -8.62%
75th Percentile £82,500 £63,125 £71,250
90th Percentile - £65,750 £76,250
South London median annual salary £70,000 £62,500 £70,000
% change year-on-year +12.00% -10.71% +16.67%

Snowflake Schema
Job Vacancy Trend in Kingston Upon Thames

Historical trend showing the proportion of permanent IT job postings citing Snowflake Schema relative to all permanent IT jobs advertised in Kingston Upon Thames.

Snowflake Schema job vacancy trend in Kingston Upon Thames

Snowflake Schema
Co-Occurring Skills & Capabilities in Kingston Upon Thames 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:

Application Platforms
1 2 (100.00%) Apache Airflow
1 2 (100.00%) Apache Spark
Cloud Services
1 2 (100.00%) AWS
1 2 (100.00%) Azure
1 2 (100.00%) Azure Synapse Analytics
1 2 (100.00%) dbt
1 2 (100.00%) GCP
1 2 (100.00%) Power Platform
1 2 (100.00%) Snowflake
Database & Business Intelligence
1 2 (100.00%) Amazon Redshift
1 2 (100.00%) BigQuery
1 2 (100.00%) Data Lake
1 2 (100.00%) Data Warehouse
1 2 (100.00%) Elasticsearch
1 2 (100.00%) Looker
1 2 (100.00%) Power BI
1 2 (100.00%) Tableau
Development Applications
1 2 (100.00%) MLflow
General
1 2 (100.00%) Analytical Skills
Job Titles
1 2 (100.00%) Senior
1 2 (100.00%) Senior Systems Engineer
1 2 (100.00%) Systems Engineer
Libraries, Frameworks & Software Standards
1 2 (100.00%) Kafka
1 2 (100.00%) LangChain
1 2 (100.00%) LlamaIndex
1 2 (100.00%) pgvector
1 2 (100.00%) PyTorch
1 2 (100.00%) scikit-learn
1 2 (100.00%) TensorFlow
Miscellaneous
1 2 (100.00%) Cloud Native
1 2 (100.00%) Clustering
1 2 (100.00%) Public Cloud
Processes & Methodologies
1 2 (100.00%) AI
1 2 (100.00%) Analytics
1 2 (100.00%) Business Intelligence
1 2 (100.00%) Data Engineering
1 2 (100.00%) Data Governance
1 2 (100.00%) Data Management
1 2 (100.00%) Data Modelling
1 2 (100.00%) Data Science
1 2 (100.00%) Dimensional Modelling
1 2 (100.00%) ETL
1 2 (100.00%) Knowledge Management
1 2 (100.00%) Machine Learning
1 2 (100.00%) Performance Tuning
1 2 (100.00%) Predictive Modelling
1 2 (100.00%) Presales
1 2 (100.00%) RBAC
1 2 (100.00%) Semantic Search
1 2 (100.00%) Storytelling
1 2 (100.00%) Systems Engineering
1 2 (100.00%) Use Case
Programming Languages
1 2 (100.00%) Python
1 2 (100.00%) SQL
Quality Assurance & Compliance
1 2 (100.00%) California Consumer Privacy Act
1 2 (100.00%) GDPR
Vendors
1 2 (100.00%) Cloudera
1 2 (100.00%) Databricks
1 2 (100.00%) Dell