3 digital jobs in high demand and their required skill sets

Image source: Andor Bujdoso – 123RF.com

“It’s not unusual to feel uncertain about the future,” says Deirdre Peach, senior talent acquisition specialist at Strider Digital. “Humans have always felt this way, but it’s how we tackle this fear of the unknown that really shapes the way forward. From a career standpoint, it’s important to view the future with an agile lens, with a willingness to adapt, upskill and change lanes if necessary. The future of jobs – and digital ones in particular – are ever-evolving and this definitely doesn’t close the door to opportunity, instead throws it wide open.”

An interesting study conducted by Dell, in collaboration with the Institute for Future, predicted that 85% of the jobs that will be available in 2030 haven’t even been invented yet.

However you look at this, it’s an exciting prospect that leaves the options for the future of work open-ended. But what about 2025? What jobs will be leading the charge? And what skills will be needed to make the cut?

Helping to paint a picture of what can be expected of digital jobs in 2025, Peach draws attention to three positions that she believes will be in high demand.

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1. Cybersecurity engineer

This will come as no surprise. Cyber threats have become commonplace in today’s business world, with companies big and small being targeted.

“The demand for cybersecurity engineers has skyrocketed over recent times and this is set to continue into 2025 and beyond,” explains Peach.

“A cybersecurity engineer is an information security professional who conducts functions that involve designing, developing and implementing highly secure network solutions. Ultimately, they protect sensitive data and systems from attacks from hackers, a function that has now moved from being a nice to have to being an absolute necessity.”

To work as a cybersecurity engineer, one needs to have a healthy mix of hard and soft skills. This role is well suited to individuals who are detail-orientated, analytical and exceptional problem solvers. Cybersecurity engineers also need to have an extensive knowledge of operating systems and security protocols, know how to code but also be able to work well in a team and think creatively too.

2. Automation engineer

This job title may sound a bit too futuristic for some, but this position is already in high demand and the next few years will only see this demand accelerate.

“Automation engineers search for ways to simplify activities for employees, consumers and businesses alike, by finding clever ways to automate specific systems,” says Peach, “and it’s innovation-focused roles like this that will be at the core of a business’ success in the future, as data analysts and business leaders look for new ways to improve efficiency.”

In order to succeed as an automation engineer, a person has to have both hard and soft skills. Programming abilities are a non-negotiable, as are leadership skills, because effective team management is crucial. The ability to problem solve and communicate successfully also ranks high on the list of skills that will get you a position in automation.

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3. Machine learning engineer

Many would probably expect that all machine learning jobs would be reserved for, well, machines, but this is a huge misconception.

“Machine learning engineers are in fact very critical members of a data science team,” says Peach. “They research, build and design the artificial intelligence tools needed for machine learning, which also involves the maintenance and improvement of artificial intelligence systems already in existence.”

Unlike many other digital jobs, there is no real entry-level route into becoming a machine learning engineer. People who occupy this position have often spent many years as data scientists or software engineers.

“But like cybersecurity and automation engineers,” Peach concludes, “people who succeed in this role have both soft and hard skills. Not only do they need to be proficient in analysing statistics, have the ability to understand and work with mathematical concepts and understand probability effectively, machine learning engineers also need to be great communicators and team players. Often, they serve as the core communicator between other data science team members and work directly with many different teams in a business.”