The 5 most important skills employers are looking for in cloud computing

Cloud technology on laptop

Cloud technology is redefining the way we do business. With cloud tech services estimated to be up by 17.3% this year and 90% of business set to use cloud tech by 2022, having the skills and abilities necessary to join the cloud service industry is an increasingly relevant skillset for many job seekers.

Being a relatively new technological territory, it requires anyone looking to find a job within cloud technology to keep up to speed with essential skills for making cloud computing as efficient as it can be.

Here are the most valuable skills for anyone in cloud computing. If you have or can acquire these skills, you will be in demand.  

1. Cloud Security

It’s essential that companies pay attention to cloud security, with cloud providers insisting that looking after the cloud is a shared responsibility between provider and business.

According to Netskope, a market leading cloud access security broker, 95% of cloud-hosted applications are facing security vulnerabilities. This means that having experience in cloud security is a valuable and in-demand skill for anyone in this field.

2. Database Management and Big Data

Cloud is the strongest competitor to on-premise systems when considering the storage, access and management of data. Cloud technology allows businesses to reap the benefits of increased scalability and flexibility with reduced operational cost and trouble-free enterprise transformation, as well as commanding a plethora of tools to process, analyse, visualise, store and manage the ceaseless amounts of Big Data. 

Any aspiring cloud-based professionals need to know the tools to deal with every aspect of data management. Big Data was originally distinguished from more traditional data and databases based on the concepts of volume, velocity and variety. Essentially, it refers to enormous data volumes that are too unwieldy for traditional databases and data tools to be able to manage. Common examples of big data are real-time credit card transactions, weather data and patterns, and Facebook feeds. Popular tools for big data storage and analytics which are in high demand for job seekers include Hadoop, MongoDB, R-programming, HPCC, Apache Storm and Apache Cassandra.

3. Programming Skills

Cloud computing is bringing a new perspective to the world of developers. If the cloud environment for app testing and development is set up correctly, it can mean shorter development and testing cycles, realistic testing environments, high-quality code and more efficient feedback loops.

While the cloud supports development and deployment of key programming technologies like Java, javascript and .Net for full stack application development, programming for the cloud itself is more often done via scripting language to automate the virtual infrastructure and deployment of applications. The most popular programming language for automation is Python. Other prevalent languages within a cloud environment for big data include Scala and Perl 6.

4. Microsoft Azure Qualification

Microsoft Azure is growing rapidly in comparison to any competitors, with a stark 154% year on year growth rate. Microsoft Azure is a highly efficient tool, providing the means to complete tasks of design, management of platforms and deployment. With Microsoft being in the public awareness with its recognisable Windows OS, the learning curve is far less steep for any users trying to develop these new skills.

Also, Microsoft has developed Azure from the start to be compliant with government security requirements, while Amazon, Google and Facebook are facing various global legal challenges over data privacy, security and market tactics, Microsoft is enjoying untrammeled growth.

5. Machine Learning and AI

Artificial Intelligence and Machine Learning skills are the icing on the cake.

Many businesses are adding AI and ML learning features to their business applications so that these technologies can be kept working and satisfying customers’ requirements. Once in place, they can increase the productivity of any business or project thanks to their connection to the previously mentioned Big Data.

ML is essentially the study of algorithms and statistical models so that computers can perform tasks based on using pattern recognition and making inferences, as opposed to relying on specific instructions. The development of machine learning is typically done using traditional robust programming languages like Java/C/C++ combined with statistical and mathematical modelling.

Examples of Machine Learning include email filtering for spam, pattern recognition of image analysis (such as searching all of Facebook for the prevalence of a corporate logo or an individual’s face). AI is continuing to expand to new frontiers such as drones mimicking insect swarm behaviour for military applications, medical diagnosis, self-driving cars, financial Chabot’s, and legal assistants. The three stages of AI are defined as Narrow AI (current stage), Generalist AI (creative capability, to solve problems it’s not directly designed to), and finally Super AI (think the Matrix, Skynet etc., it’s time to move into your bunker). For now, AI development is less than 1% of the job market but growing rapidly.

 To find out more about opportunities in cloud computing or the tech industry, get in touch with me today.