Cloud professional is one of the most coveted jobs in 2018.

The cloud industry continues to grow at a breakneck pace, and the demand for individuals who have cloud computing skills and who can maintain cloud systems to develop software, finetune infrastructure, manage hardware and applications is only increasing.

In the meantime, the lack of the cloud talent becomes increasingly apparent. The cloud computing skills gap is growing quickly, and businesses lose millions in revenue every year.

Quoting the research by the London School of Economics:

Nearly three quarters of IT decision makers (71%) believe their organizations have lost revenue due to a lack of cloud expertise.

The same research states that the lack of cloud professionals costs businesses up to $250m per year.

All of that basically means that cloud skills are badly needed in the workplace.

But where should you start if you want to become a cloud professional? Which areas of expertise should you dig in to stay competitive in 2018?

In this article, I will list six top cloud skills in demand. Master these skills and you will become literally unstoppable.

1. Database Management and Big Data

According to McAfee research, 57% of businesses adopted hybrid cloud in 2017, with ~80% of IT leaders aiming to invest in cloud solutions in 2018-19.

And it is no wonder why.

Cloud is the strongest competitor to on-premise systems when it comes to storing, accessing, and managing data, which is one of the most important assets of any organization.

Enterprises opt for using Big Data systems in the cloud, because:

  • Cloud commands a variety of tools to store, process, analyze, visualize, and administer the unlimited amount of Big Data
  • Cloud resolves the issue of creating highly scalable Big Data analytics solutions through built-in toolchains
  • Cloud allows taking advantage of so-called “dark data,” which is challenging to collect, store, and process with on-premise solutions
  • Cloud enables businesses to enjoy the benefits of increased scalability and flexibility, reduced operational cost, and easier enterprise transformation

Aspiring cloud professionals should know the tooling to do all of that.

Here is when they can choose between cloud database services provided by major cloud providers (Amazon Web Services, Google Cloud Platform, and Microsoft Azure) and open source database platforms (MongoDB, Redis, etc.)

As a rule, the first are much easier to comprehend, since they support multiple variants of SQL for writing queries and running server instances. That said, you do not necessarily have to know Hadoop, Apache Beam, or Spark to manage Big Data.

In the meantime, the latter may be used if your IT organization needs a completely customizable solution or has to comply with strict data security & data privacy requirements.

Note: Bear in mind that enterprises may fall victim to cloud’s popularity and adopt it when they actually do not need it. Should they do so before business leaders have thought through all the consequences, serious issues in data and DB management will be inevitable.

2. AI & Machine Learning

AI & Machine Learning skills are no longer nice-to-haves, but essential requirements to the position of a cloud computing expert.

Here is why:

  • Enterprises are pressed to draw valuable insights from data in a cost-efficient manner (i.e. using AI & ML capabilities)
  • Businesses have to quickly add AI & ML learning features to their applications to satisfy customer needs
  • SMEs and corporate-level enterprises may not have the resources and talent to build their own AI & ML solutions

And here is when major cloud vendors come to the rescue — they supply businesses with powerful AI & ML tools, which otherwise are too complex and costly to develop.

AI & ML have also made it to the list of top cloud computing skills because they allow to greatly increase time to value and time to market due to their natural connection with Big Data.

AWS, Microsoft, Google, and other cloud vendors make sure that Big Data capability is nicely integrated with AI & ML to:

  • Feed more data to existing ML models
  • Create larger training datasets for new ML models
  • Enable efficient analysis of connections and relationships in data
  • Build higher-quality ML models
  • Deliver more accurate, data-based predictions

In that context, investing your time in learning at least the basics of AI & ML in the cloud totally makes sense.

3. Application Security

Security should be every cloud professional’s top priority.

Cloud is on a surge right now, and while the adoption has already hit the mid-market, the implementation remains at the depth of cloud’s core benefits without having to set up proper security configurations in the first place.

According to Netskope research, ~95% of cloud-hosted applications in the EU are vulnerable from a security standpoint.

As stated in recent research by McAfee, 36% of organizations that migrate their applications to the cloud cannot protect them from malware and bad actors.

That is why, cloud security professionals are very much needed right now.

Organizations need talented individuals who have the right skills in place to manage multiple cloud platforms:

  • Control and fine tune the security settings
  • Utilize the available security tools (e.g. built-in security tools provided by AWS and other cloud vendors)
  • Protect infrastructure and data from major vulnerabilities in the security layer.

That being said, they need professionals who know the cloud platforms and specifics of how their shared responsibility models work in varying environments. That is, you have to know which part is the responsibility of the cloud vendor and which part is up to you to set up and manage.

The image below demonstrates the shared responsibility model for AWS:

Another important area of expertise here is GDPR.

As a cloud professional, you should be able to ensure the privacy of user data using cloud tools at hand. For instance, if we think AWS, you should be able to use the following tools to ensure compliance with GDPR: AWS Config, AWS CloudTrail, AWS Inspector, and Amazon EC2.

4. Containers

According to The Portworx Annual Container Adoption survey, 32% of organizations invested over $500K in container technology in 2017.

Here is why:

Containers are more agile and flexible than virtual machines. They allow to easily virtualize applications, develop and deploy microservices, which makes operations more efficient by default.

Containers are a must-have skill for cloud computing professionals.

They should know to manipulate multiple container orchestration tools — Docker, Amazon ECS, Google Container Engine, Azure Container Service, Kubernetes — to deploy and manage cloud solutions in real time.

5. Cloud Migration

According to RightScale survey, 96% of IT leaders report that their organizations use cloud technology in some form or fashion in 2018.

This basically means two things:

  • Both SMEs and corporate-level enterprises are quickly migrating their applications to the cloud or hybrid cloud systems
  • They use only selected features and have not fully embraced the cloud yet due to some migration challenges and lack of knowledge

Cloud professional’s role here is to assist organizations in migrating their applications and operations to the cloud while fully complying with security, data privacy, infrastructure and environment requirements.

Once again, to ensure effective migration, cloud professionals should have major cloud platforms at their fingertips.

6. Cloud App Development

Another significant aspect of working in the cloud is application development.

Since cloud offers amazing scalability, flexibility, and agility capabilities at a lower cost, small businesses and enterprises opting to move their app development and testing processes to the cloud.

If the cloud environment for application development and testing is properly set up, organizations enjoy:

  • Shorter development and testing cycles
  • Realistic testing environments
  • Higher-quality code
  • Faster time to market
  • More efficient feedback loops

In other words, cloud allows organizations to embrace DevOps.

To support the development part, cloud professionals should know how to code using Python, C#, Java, Scala, PHP, Ruby, Perl, or any other programming language they are comfortable with.

Bear in mind: While you can use any language you want, in fact every platform usually has a main language. For instance, you need C# for Azure, Python for AWS, and Java for Elastic Beanstalk.


Cloud computing skills are in high demand.

While the cloud is quickly developing as a technology and as a service, the market lacks qualified cloud professionals.

Small & medium businesses and enterprise-level companies cry out for individuals who not only know the basics of using major cloud platforms, but who are equipped to work with Big Data systems, know how to efficiently gain insights from data, maintain app’s security and compliance, and migrate any part of an organization’s software for further development and testing in the cloud.

The demand for cloud computing expertise is driving up salaries.

According to Glassdoor: The median base salary for a Cloud Engineer is $95K, while a Cloud Computing Expert earns $138K on average.

Thus, those who can learn how to manage cloud database tools, utilize Big Data with AI & ML, manipulate containers for faster deploys, migrate software to the cloud, and ensure cloud development process are perfectly positioned to land well-paying jobs.

Start mastering these skills now to position yourself for future success in the IT industry!

What are your thoughts about the cloud? What cloud skills would you recommend to learn? What are the most in-demand cloud computing skills in your organization?

Nick Kartman

Technology evangelist passionate about DevOps, Big Data, ML, and Cloud. An avid contributor to the Squadex blog.