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15 January 2026 Addressing the data center talent crisis Fabrizio LandiniGlobal Data Center Segment Leader
Discover the benefits of IT/OT convergence, plus our roadmap for achieving it in your own data center operations.
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Long story short There is a considerable deficit in electrical and mechanical engineering talent. In response, businesses, from hyperscalers to small-scale enterprises, must develop new strategies to attract, develop, and retain talent. Why it matters Firms’ ability to deploy and scale advanced technologies like AI depends on access to high-quality engineering talent that can help them design, build, and maintain and optimize data centers. Confronting the talent crisis The Construction Industry Training Board has predicted that the UK needs to recruit 50,300 additional workers annually over the next five years to support the data center boom. There’s a similar picture in other regions targeting ambitious build-outs. This shortfall in qualified electrical, mechanical, and maintenance engineers could have significant consequences for data center operations – putting safety and service continuity at risk. Getting to grips with the characteristics and potential responses to this crisis starts with understanding the nature of the work being done. In particular, the kinds of skills required to deploy new data center infrastructure depends on what phase of a project a worker is involved in. Planning and design require high levels of technical expertise: you need people who can produce single line diagrams, and understand the physics of data centers, from air flow to heat management. Generally, this involves Bachelor's and Master's degrees, which take years to complete. Building physical infrastructure comes down to actioning plans in line with particular standards. Installation entails following a particular manual to the letter. Training in this area entails specific certifications that can be acquired after high school or equivalent education. For example, the NESD electrical certification takes 2 to 3 months to complete. Optimizing and maintaining data centers is the least skill-intensive work of these phases. It’s still skilled labor of course, but data centers have relatively few moving parts and single points of failure. As long as they are designed well in the first place and appropriate procedures are followed, many systems won’t fail for 20 years or more. As a result, upskilling in this area is relatively quick. Training and retaining talent Data center operators need talent across the engineering spectrum, from designers and builders to maintenance engineers and electricians. With this skills matrix in mind, organizations must assess what the best approach to training and retaining talent is for them. This varies depending on their size and appetite for managing operations in house, as opposed to working with third-party partners. Hyperscalers are the ones leading the charge when it comes to data center engineering talent. They have the resources and the global footprint required to nurture talent. This includes everything from sponsoring people to undertake 3 or 4-year programs, and hiring them afterwards, to upskilling individuals who show high engineering potential in their maintenance work. Apprenticeships and in-house training have a key role to play in enabling firms to progressively support talent from high school onwards. “Apprenticeships and in-house training have a key role to play in enabling firms to progressively support talent from high school onwards.” Tier-one colocators are also driving change. They often offer internships and investment programs that similarly nurture talent and prepare them for the challenges of data center operations. Tier-two and three colocations are generally less programmatic in their approach – they have less capital to invest in these areas. Instead, they primarily hire talent from competitors, often paying a premium during the hiring process, but benefiting from the training and certifications they have acquired up to that point. Despite the work being done, there’s still a shortfall – one that cannot be filled by traditional STEM programs or internships. Industry and government must do more to encourage talent into suitable pathways. One potential growth area is trade schools that focus on the specific skills necessary to work with data centers. Not everyone can study for multiple years, so supporting, partnering with, and actively hiring from these institutions will help make the most of the talent available. New operating models and solutions Fortunately, the same technologies that are placing heavy demands on data center infrastructure can help address the talent shortfall. Automation and AI-driven insights can relieve data center staff of many routine and manual processes, enabling them to focus on the high-priority, high-impact tasks that matter the most. AI tools also make it possible to monitor workload distribution, dynamically adjusting resources to meet real-time demand, and identifying where efficiencies could be made. As well as managing power, AI is a great integrator. It can aggregate and analyse data across disparate systems - from software to infrastructure to cooling - to help employees make the right trade-offs and identify opportunities for cost saving across the business. Previously time-consuming decision-making processes, like Scope 1, 2 and 3 emissions reduction, can be augmented and even automated with the help of AI. In parallel, new operating models are reducing the burden on onsite engineers thanks to modular, prefabricated, and containerized designs. Operators give their specifications to a manufacturer, and the build takes place in factories that benefit from automation and advanced robotics. From there, mobile substations are transported to sites on 18-wheelers – all that’s left to do onsite is lock the containers to concrete slabs and connect them to a power source. It’s a “plug and play” solution that dramatically reduces the inefficiency of conducting complex work in the field. Hitachi Systems conducted one such project in Japan. By deploying containerized units with high-load servers, server rooms, and base stations, we were able to meet the demand of new generative AI workloads with a streamlined process. Each unit was supported by generators, water-cooled air conditioning units, fire extinguishing systems, and more – everything a data center needs to operate effectively. The project took only 50% of the time it would take to build infrastructure onsite – just 18 months, rather than 36. That’s half as much human resource demand. This kind of operational efficiency can be delivered across a range of projects. For example, Hitachi fast tracked a grid connection to support Dublin’s data center boom. It delivered a fully integrated 220/110 kV substation with gas-insulated switchgear in just 18 months – well ahead of typical timelines. This reduced the build-out time of data centers in the hub by 66% and ensured reliable 24/7 power for the city’s expanding ecosystem. New innovations can also help operators to upskill existing talent. Digital twins can be used for training; just as pilots use flight simulators to learn to fly, engineers can practice assembling, installing or repairing data center infrastructure in virtual environments. This doesn’t replace the need for formal training and accreditation. But the talent crisis isn’t going anywhere, and we need to use every tool at our disposal.
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Own the conversation Ask the big question: Have we entered a battle for talent? Is hiring engineers from one another a sustainable way to address the shortfall? Disrupt your feed: Over time, we may see the rise of a workforce as a service model, by which a centralized pool of people is allocated to infrastructure. This could even be organized on a national level – just as countries implement policies for energy and GPUs, they will develop strategies for sourcing engineers. Drop this fact: Almost two thirds (63%) of data center operators report difficulties finding and retaining qualified staff.
