Skills and experience
Skills and experience
Skills and experience
What are the top 10 AWS areas candidates are experienced with?
| 1. Compute | 61% |
| 2. Database | 57% |
| 3. Storage | 56% |
| 4. Serverless | 50% |
| 5. Containers | 47% |
| 6. Networking & Content Delivery | 40% |
| 7. Security, Identity, & Compliance | 39% |
| 8. Application Integration | 34% |
| 9. Developer Tools | 34% |
| 10. Migration & Transfer | 29% |
Expert Insight
Credera was the winner of Best AWS Partner To Work For (UK) at the Digital Revolution Awards 2023. We caught up with their AWS Competency and Capability Lead, Peter Kiernan, to learn more about his predictions for AI on AWS after over 15 years of designing and managing the delivery of complex IT solutions for clients across a range of industries.
One of the biggest benefits of generative AI tools is that it opens clients’ minds to the broader capabilities of AI and machine learning. Demand for professionals with a deep understanding of these tools who can incorporate them as part of a well-architected AWS environment is growing.
For professionals, the opportunities to learn and help clients exploit the value of these services are huge, and an AWS professional with this expertise is sure to stand out from the crowd. Very rarely is there an opportunity with new technologies to ‘get in on the ground floor’ – this is one of them.
Any solution leveraging AWS’ AI services is still highly reliant on a well-architected platform with strong technical and procedural processes. AI services are most effective when they can access a broad set of data points – these must be well-understood and controlled.
For AWS professionals, there is already a wealth of training material available. AWS offers several free courses and local in-person training events aimed at a range of backgrounds, including business and non-technical audiences.
Enhancements to AI services already mean that elements of certain day-to-day roles are no longer required. For AWS SysAdmins, this might include tasks such as analyzing server logs or monitoring resources. For Data Scientists, Amazon SageMaker already simplifies the process of building and training AI/ML models. Both of these examples still require specialist skills, but manual and repetitive tasks can now be automated.
A positive work environment can be fostered through individuals recognizing the benefits of retraining and learning how to exploit these services. For the professional, they will build relevant and marketable skills, whilst benefiting from all the positives that AI solutions bring to their day-to-day role.
Expert Insight
Credera was the winner of Best AWS Partner To Work For (UK) at the Digital Revolution Awards 2023. We caught up with their AWS Competency and Capability Lead, Peter Kiernan, to learn more about his predictions for AI on AWS after over 15 years of designing and managing the delivery of complex IT solutions for clients across a range of industries.
One of the biggest benefits of generative AI tools is that it opens clients’ minds to the broader capabilities of AI and machine learning. Demand for professionals with a deep understanding of these tools who can incorporate them as part of a well-architected AWS environment is growing.
For professionals, the opportunities to learn and help clients exploit the value of these services are huge, and an AWS professional with this expertise is sure to stand out from the crowd. Very rarely is there an opportunity with new technologies to ‘get in on the ground floor’ – this is one of them.
Any solution leveraging AWS’ AI services is still highly reliant on a well-architected platform with strong technical and procedural processes. AI services are most effective when they can access a broad set of data points – these must be well-understood and controlled.
For AWS professionals, there is already a wealth of training material available. AWS offers several free courses and local in-person training events aimed at a range of backgrounds, including business and non-technical audiences.
Enhancements to AI services already mean that elements of certain day-to-day roles are no longer required. For AWS SysAdmins, this might include tasks such as analyzing server logs or monitoring resources. For Data Scientists, Amazon SageMaker already simplifies the process of building and training AI/ML models. Both of these examples still require specialist skills, but manual and repetitive tasks can now be automated.
A positive work environment can be fostered through individuals recognizing the benefits of retraining and learning how to exploit these services. For the professional, they will build relevant and marketable skills, whilst benefiting from all the positives that AI solutions bring to their day-to-day role.
Cross-training
Over half (56%) of those surveyed have cross-trained into AWS, having previously worked with a competitor product.
Top 5 competitor products used before NetSuite:
Is a degree necessary for a career in AWS?
Our key findings report contains highlights from this year’s Careers and Hiring Guide, plus our salary tables allow you to compare your salary or benchmark your teams’ salaries no matter their role in the AWS ecosystem.
Our key findings report contains highlights from this year’s Careers and Hiring Guide, plus our salary tables allow you to compare your salary or benchmark your teams’ salaries no matter their role in the AWS ecosystem.
Our key findings report contains highlights from this year’s Careers and Hiring Guide, plus our salary tables allow you to compare your salary or benchmark your teams’ salaries no matter their role in the AWS ecosystem.
