Database Architects




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Automation risk
Low Risk (21-40%): Jobs in this level have a limited risk of automation, as they demand a mix of technical and human-centric skills.
More information on what this score is, and how it is calculated is available here.
User poll
Our visitors have voted they are unsure if this occupation will be automated. However, employees may be able to find reassurance in the automated risk level we have generated, which shows 36% chance of automation.
What do you think the risk of automation is?
What is the likelihood that Database Architects will be replaced by robots or artificial intelligence within the next 20 years?
Sentiment
The following graph(s) are included wherever there is a substantial amount of votes to render meaningful data. These visual representations display user poll results over time, providing a significant indication of sentiment trends.
Sentiment over time (yearly)
Growth
The number of 'Database Architects' job openings is expected to rise 10.3% by 2031
Updated projections are due 09-2023.
Wages
In 2022, the median annual wage for 'Database Architects' was $134,870, or $64 per hour
'Database Architects' were paid 191.2% higher than the national median wage, which stood at $46,310
Volume
As of 2022 there were 62,470 people employed as 'Database Architects' within the United States.
This represents around < 0.001% of the employed workforce across the country
Put another way, around 1 in 2 thousand people are employed as 'Database Architects'.
Job description
Design strategies for enterprise databases, data warehouse systems, and multidimensional networks. Set standards for database operations, programming, query processes, and security. Model, design, and construct large relational databases or data warehouses. Create and optimize data models for warehouse infrastructure and workflow. Integrate new systems with existing warehouse structure and refine system performance and functionality.
SOC Code: 15-1243.00
Resources
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Comments
Similarly, relational structures are not performant for graph data at usable levels. AI will have plenty of examples, both internal to an organization and via accepted issue-specific models, to architect and tune storage.
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