Tech skills are increasingly in demand in the job market as technology plays a vital role in many industries. And it’s very important to acquire these skills in today’s world to be more employable and also make passive income for yourself. If you are looking for any of these skills you can acquire, there are a handful of them such as programming languages (like Python, Java, and C++), web development (HTML, CSS, JavaScript), database management (SQL), and working with computer hardware and software. The most interesting thing is that these skills are very high-paying skills.


What are the top Demand Tech Skills?

The top in-demand tech skills vary depending on the industry and job market, but some skills that are generally considered in high demand include:

  1. Cloud computing (AWS, Azure, Google Cloud)
  2. Artificial intelligence (AI) 
  3. Data analysis and visualization
  4. Cybersecurity
  5. Full-stack development (JavaScript, HTML, CSS, and a back-end language such as or Java)
  6. Network and information security
  7. Software development (Java, Python, C++)
  8. Big data (Hadoop, Spark)
  9. Development operations (DevOps)
  10. Mobile app development (iOS and Android)
  11. Technical writing
  12. Product management
  13. Project Management
  14. Digital marketing
  15. Machine learning (ML)


1. Cloud computing (AWS, Azure, Google Cloud)

Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale.

You can use cloud computing to access, manage and store data, and run applications and services on remote servers, rather than on a local computer or on-premises server. The most common types of cloud computing services are Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). Examples of cloud providers include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).



2. Artificial intelligence (AI)

Artificial intelligence (AI) is a broad field of study that includes machine learning (ML) as one of its components. AI involves the development of computer systems that can perform tasks that would normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.


3. Data analysis

Data analysis is the process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data visualization is the practice of creating visual representations of data to make it more understandable and interpretable. Together, data analysis and visualization allow for the exploration and understanding of complex data sets. Common tools used for data analysis and visualization include Excel, R, Python, and Tableau.

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4. Full-stack development

Full-stack development refers to the practice of developing both the front-end and back-end portions of an application. The front-end, also known as the client-side, is responsible for the user interface and the way the application looks and feels.

This is typically built using JavaScript, HTML, and CSS technologies. The back end, also known as the server side, is responsible for the application’s logic and data management. This is typically built using programming languages such as Java, Python, or Ruby. A full-stack developer is someone who is proficient in both front-end and back-end development and can work on both sides of an application.

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5. Cybersecurity

Cyber security refers to the practices and technologies that are used to protect computer systems, networks, and data from unauthorized access, use, disclosure, disruption, modification, or destruction. It involves identifying and managing the various threats to an organization’s digital assets, such as malware, ransomware, phishing, and hacking. To protect against these threats, cybersecurity professionals use a combination of technical controls, such as firewalls, intrusion detection systems, and encryption, as well as non-technical controls, such as employee training and incident response plans. Cybersecurity is becoming increasingly important as more and more organizations rely on digital systems and the internet to conduct their business.



6. Network and information security (NIS)

Network and Information security is a sub-field of cybersecurity that focuses on protecting an organization’s computer networks and the information that is stored and transmitted on those networks. NIS involves a variety of security measures that are designed to protect against unauthorized access, use, disclosure, disruption, modification, or destruction of networked information and systems.

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These measures include network security technologies such as firewalls, intrusion detection systems, and virtual private networks (VPNs), as well as security policies and procedures such as security awareness training, incident response planning, and regular security audits. NIS also includes protecting against threats such as malware, phishing, and hacking, and ensuring the confidentiality, integrity, and availability of data.



7. Software development

Software development is the process of designing, creating, testing, and maintaining software using programming languages. There are many programming languages that are commonly used in software development, such as Java, Python, and C++.

  • Java is an object-oriented, class-based, and concurrent programming language that is specifically designed to have as few implementation dependencies as possible. It is widely used for building enterprise-level applications and can be found in many devices such as mobile phones, televisions, Blu-ray players, and more.
  • Python is a general-purpose programming language that is widely used for web development, scientific computing, data analysis, artificial intelligence, and more. It is known for its clear syntax, readability, and ease of use, making it a popular choice for beginners and experienced developers alike.
  • C++ is a general-purpose, high-performance programming language that is widely used for system and application programming. It is an extension of the C programming language and provides object-oriented features such as classes and objects. C++ is commonly used in the development of operating systems, embedded systems, video games, and other high-performance applications.

All of these languages have their own unique features and are suitable for different types of software development projects.



8. Big data (Hadoop, Spark)

Big Data refers to the large and complex data sets that organizations need to store, process, and analyze in order to extract insights and make better decisions. Big data typically includes structured and unstructured data and can come from a variety of sources such as social media, sensor data, and log files.

  • Hadoop is a popular open-source framework that is widely used for big data processing. It allows organizations to store and process large data sets across a cluster of commodity hardware. Hadoop’s primary component is the Hadoop Distributed File System (HDFS), which allows for the storage of very large data sets across multiple machines. Another important component of Hadoop is the MapReduce programming model, which allows for the parallel processing of large data sets.
  • Apache Spark is another open-source framework for big data processing, it’s known for its in-memory data processing capabilities which makes it faster than Hadoop. Spark provides a set of high-level APIs for data processing, machine learning, and graph processing, and it can read data from various sources such as HDFS, Cassandra, Hbase, and S3. Spark also provides a built-in module for SQL and streaming data processing, making it more versatile than Hadoop.


Both Hadoop and Spark are widely used in big data ecosystems, and they complement each other. Hadoop provides a distributed file system for storing data and Spark provides the ability to perform in-memory data processing on top of Hadoop.



9. DevOps (Development Operations)

DevOps is a software engineering culture and practice that aims to bring development and operations teams together to improve collaboration and communication and to automate the process of software delivery. DevOps emphasizes the use of automation and monitoring at all steps of the software development process, from development and testing to deployment and infrastructure management. This helps organizations to quickly and efficiently deliver software updates and new features to customers while maintaining a high level of quality and security.

There are several key practices that are associated with DevOps. One of the most important is a continuous integration and continuous delivery (CI/CD), which is the practice of automatically building, testing, and deploying software changes to a staging or production environment.

Another important practice is infrastructure as code (IaC), which is the practice of using code to manage and provision infrastructure, such as servers and network devices. This allows for more efficient and reliable management of infrastructure, as well as better collaboration between development and operations teams. Other practices include configuration management, monitoring and logging, and containerization and orchestration.

DevOps is not only a set of tools, but it’s also a culture and mindset that helps organizations to achieve faster time to market, better quality, and more reliability in the software development process.



10. Mobile app development (iOS and Android)

Mobile app development is the process of creating software applications that run on mobile devices such as smartphones and tablets. There are two major mobile operating systems: iOS, which is used on Apple devices such as the iPhone and iPad, and Android, which is used on a wide variety of devices from different manufacturers.

  • For iOS app development, developers typically use Swift or Objective-C programming languages and the Xcode integrated development environment (IDE). Swift is a modern programming language developed by Apple, it is known for its easy-to-read syntax, and for its strong type system. Objective-C is an older programming language also developed by Apple, it’s still widely used and supported by Apple.
  • For Android app development, developers typically use Java or Kotlin programming languages and the Android Studio IDE. Java is a well-established programming language, it’s widely used for Android app development and other types of development. Kotlin is a modern programming language developed by JetBrains, it’s more concise and expressive than Java, and it’s fully interoperable with Java, which makes it a great option for android app development.
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Both iOS and Android have their own set of guidelines, best practices and tools, but many of the concepts and skills learned in one platform can be applied to the other.

Additionally, there are many cross-platform mobile app development frameworks that allow developers to create apps for both iOS and Android using a single codebase, such as React Native, Xamarin, and Flutter.



11. Technical writing

Technical writing is the practice of creating clear, accurate, and user-friendly documentation for technical products, processes, and systems. Technical writers create a wide range of documents, including user manuals, installation guides, help files, and online help systems, as well as more complex documents such as technical reports, white papers, and proposals.

Technical writing requires a combination of technical knowledge and writing skills. Technical writers need to have a deep understanding of the products, processes, or systems they are documenting, as well as the ability to explain complex technical concepts in a clear and simple way. They must also be able to organize information in a logical and user-friendly manner and create documents that are visually appealing and easy to navigate.


Some of the key skills required for technical writing include:

  • Strong writing and editing skills
  • Ability to translate technical concepts into clear, concise language
  • Understanding of the target audience and the ability to write for them
  • Experience with document design and layout
  • Familiarity with technical tools such as screen capture software, help authoring tools, and version control systems
  • Knowledge of specific industry and technical subject areas.
  • Technical writing is an important field that helps to bridge the gap between technical and non-technical audiences, making complex information accessible and understandable for all.

You can become a professional technical writer or a Ghost writer by taking this course


12. Product management

Product management is the process of overseeing the development and life cycle of a product, from the initial concept to the end of its life. Product managers are responsible for defining and maintaining the product vision and strategy, and for working with cross-functional teams to bring the product to market.


The key responsibilities of a product manager include:

  • Defining the product vision and strategy: This includes identifying and prioritizing customer needs, setting product goals, and creating a product roadmap.
  • Gathering and analyzing the market and customer data: This includes conducting market research, analyzing customer feedback, and monitoring competitors.
  • Defining product requirements: This includes creating detailed specifications for the product and working with engineering, design, and marketing teams to ensure that the product meets customer needs.
  • Managing the product development process: This includes working with cross-functional teams to ensure that the product is delivered on time and within budget and that it meets quality and performance standards.
  • Launching and promoting the product: This includes creating and executing a go-to-market plan and working with marketing and sales teams to ensure that the product is well-positioned in the market. Managing the product life cycle: This includes monitoring product performance, identifying opportunities for improvement, and making decisions about when to end-of-life the product.
  • Product management is a strategic function that requires strong leadership, communication, analytical and problem-solving skills. Product managers need to have a good understanding of the market and the customers, as well as the ability to work effectively with cross-functional teams.



13. Project Management

Project management is the practice of planning, organizing, and overseeing the execution of a specific short-term project with a defined start and end, aimed at achieving specific goals and objectives. Project management is a critical function that helps organizations to achieve their goals and objectives by delivering projects on time, within budget, and to the required quality standards.


The key responsibilities of a project manager include:

  • Defining project scope: This includes identifying project objectives, deliverables, and constraints.
  • Developing a project plan: This includes creating a detailed project schedule, identifying and allocating resources, and creating a project budget.
  • Managing project execution: This includes monitoring and controlling project progress, identifying and managing risks, and ensuring that the project is delivered on time, within budget, and to the required quality standards.
  • Communicating with stakeholders: This includes keeping stakeholders informed of project progress and issues and managing stakeholder expectations.
  • Managing project changes: This includes identifying, evaluating, and implementing changes to the project plan as needed.
  • Closing the project: This includes completing all project deliverables, obtaining final acceptance from stakeholders, and conducting a project post-mortem to identify lessons learned for future projects.
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Project management requires strong leadership, communication, planning, and problem-solving skills. Project managers need to be able to work effectively with cross-functional teams, and manage complex and dynamic projects with multiple stakeholders.



14. Digital marketing

Digital marketing is the practice of promoting products, services, or brands using digital channels such as the internet, social media, search engines, email, and mobile apps. The goal of digital marketing is to reach and engage with customers where they spend most of their time, which is increasingly online.


Some of the key practices of digital marketing include:

  • Search engine optimization (SEO): This is the practice of optimizing a website or webpage to rank higher in search engine results pages (SERPs) in order to increase visibility and drive more traffic to the site. Search engine marketing (SEM): This is the practice of using paid advertising on search engines such as Google or Bing in order to drive more traffic to a website.
  • Social media marketing: This is the practice of using social media platforms such as Facebook, Twitter, Instagram, and LinkedIn to promote products, services, or brands.
  • Email marketing: This is the practice of using email to promote products, services, or brands, and to build relationships with customers.
  • Content marketing: This is the practice of creating and distributing valuable, relevant, and consistent content in order to attract and engage with a target audience.
  • Affiliate marketing: This is performance-based marketing where a business rewards one or more affiliates for each visitor or customer brought about by the affiliate’s own marketing efforts.
  • Analytics and measurement: This includes the practice of tracking, measuring, and analyzing the performance of digital marketing campaigns in order to optimize and improve results.

Digital marketing requires a combination of creativity, technical skills, and analytical thinking. Successful digital marketers need to have a deep understanding of the digital landscape and how to leverage it to reach and engage with customers in a meaningful way.



15. Machine learning (ML)

Machine learning (ML) is a subset of AI that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without explicit programming. ML is used in a wide range of applications, such as image and speech recognition, natural language processing, and self-driving cars.




What are the Benefits of having Tech skills?

Having tech skills can provide a lot of benefits, including:

    1. Increased employability: Many industries now require employees to have at least basic tech skills, so having them can make you more attractive to potential employers.
    2. Career advancement: Having tech skills can open up new opportunities for career advancement, such as promotions or leadership roles.
    3. Higher earning potential: People with tech skills often earn higher salaries than those without, particularly in fields like software development, data analysis, and IT.
    4. Entrepreneurial opportunities: Tech skills can also be used to start your own business, create a product, or develop a service.
    5. Improved problem-solving and critical thinking: Learning and using technology can help you develop skills in problem-solving, critical thinking, and creativity.
    6. Staying current: Technology is constantly changing, so having tech skills can help you stay current and relevant in your field.

What are the Challenges of tech Skills?

Having tech skills can come with a lot of challenges, including:

      1. Keeping up with updates and changes: Technology is constantly evolving, which can make it difficult to keep your skills current.
      2. Limited opportunities in certain areas: Some regions or industries may not have as much demand for certain tech skills, which can limit job opportunities.
      3. High competition: The tech industry is highly competitive, which can make it difficult to land a job or secure a promotion.
      4. Burnout: The tech industry can be fast-paced and demanding, which can lead to burnout if you’re not careful.
      5. Cost of learning: Some tech skills require expensive software or courses that can be costly to acquire.
      6. Difficulty learning: Some people may find it challenging to learn new technologies, particularly if they are not familiar with the concepts or have trouble grasping technical details.
      7. Difficulty in adapting to new technology: It can be difficult to adapt to new technology, particularly for older workers or those who are not as tech-savvy.
      8. Difficulty in finding the right resources: Finding the right resources to learn a new tech skill can be challenging, particularly if you are not sure where to look.


End Note

Here you have it, top 15 in-demand tech skills. And it’s worth noting that the demand for these skills can change over time depending on the market condition, Industry adoption, and new technologies.



A passionate web developer, tech blogger and Blockchain enthusiast... I love giving solutions through my writings on my leisure time. Feel free to reach me via email for collaboration etc.
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