12 IT positions give employers a headache

Entering a new decade, CIOs continue to assume greater responsibility for many strategic business tasks. With that great responsibility, it is necessary to find the talent with the skills necessary to drive those strategic initiatives.

Entering a new decade, CIOs continue to assume greater responsibility for many strategic business tasks, including those related to cybersecurity, analysis and data science, AI / machine learning.

With that enormous responsibility, it is necessary to find the talent with the skills necessary to drive those strategic initiatives. Here are the 12 most difficult IT positions to recruit.

12 IT positions give employers a headache

According to the latest survey, 39% of IT leaders predict that it will be difficult to find people with good security skills by 2020. Other notable requirements such as design thinking, DevOps and Agile skills. flexible software development solutions so they can reach users as soon as possible) are all considered hiring challenges in the coming year.

Here are 12 areas that IT leaders predict will be difficult to find the most suitable skilled person this year:

Network security: 39%
Data science / analysis: 35%
AI / machine learning / RPA: 31%
Integration / cloud services: 18%
Inheritance technology: 18%
DevOps / DevSecOps / Agile processes: 17%
Internet of things: 17%
Cloud architecture: 16%
Design thinking / UX: 16%
Software engineer: 15%
Application development: 15%
Multi-cloud management: 15%

How important is the employee's flexibility and experience?

Security remains an important priority for CIOs. In the world of Hybrid Cloud, teleworking, BYOD and many other technologies that extend the boundaries of enterprise networks, more resources are needed to ensure that networks, data and assets are protected.

A recent study found that 70% of knowledge workers living in urban areas said they would move to more remote areas if they could work at a comparable level. Employers may consider hiring retired or temporarily unemployed people to look after their children. They can work several hours a week in non-traditional environments, provided they are skilled enough to meet the job requirements.

Employers should consider the employee's experience, like every interaction that employee has with the company during the entire working period until retirement and try to create a positive environment where people have I can do my best.

The key to this is to provide learning and development opportunities, promote diversity and inclusion. Most importantly, it is necessary to eliminate inhibitors for employees, by allowing them to access the tools they need and prefer to use to perform the best job, wherever they are, into any when.

Utilize resources from within

12 IT positions give employers a headache Picture 2 — Utilize resources from within

Security is a major challenge for global companies, due to the complexity and the variety of rules and regulations available. The source of customer experience is also hard to find.

NTT Data Services addresses this problem by piloting an application that allows employees to explore company-wide opportunities and nominate themselves for those roles.

They will be able to see how their skills and experience match the requirements of each position, receive courses and read recommendations to close the skill gap, etc.

The power of improving skills

Data scientists, data engineers, security experts and full-stack developers (who are in charge of both front-end and back-end) are challenging positions for employers.

For every technology company, the person in charge of engineering is more important than ever. With fierce competition for limited resources, it is essential to provide advanced opportunities and learn new skills.

Reduce pressure with technology

At BMC Software, CIO Scott Crowder is taking advantage of automation to help reduce the pressure to complete certain IT tasks, especially in the field of Big Data analysis and data science.

Technology is constantly evolving and AI is currently being used to build, analyze, and visualize data models.

It is undeniable of course the human role in explaining and summarizing the most important things from the data, but applying automation to a number of phases will help a lot.