Top software engineering skills to learn in 2025

Software engineering is evolving fast, and what made you stand out two years ago might not cut it in 2025. With AI now part of everyday workflows, cloud platforms taking centre stage, and security expectations rising, knowing what skills are actually in demand is essential if you're thinking about your next role.

In this blog, we break down the top software engineering skills that employers are actively hiring for in 2025. From programming languages and cloud tools to AI integration and soft skills, this guide will show you where to focus your efforts to stay competitive. Whether you’re an experienced developer or early in your career, these are the areas worth investing in.

What are software engineering skills?

Software engineering skills are the technical and non-technical abilities that help engineers design, build, maintain and scale software systems. These include hands-on skills like writing code, managing cloud infrastructure or deploying through CI/CD pipelines, but also soft skills such as teamwork and time management.

Hiring managers now look for software engineers who bring more than just coding ability. They want professionals who understand systems thinking, communicate clearly, and can collaborate across disciplines. In short, software engineer skills are a mix of hard skills (the tools and tech) and soft skills (how you work with others). Both are key to progressing your career.

If you're wondering how to sharpen these skills or which ones to focus on, we've got you covered in the sections below.

Hard skills for a software engineer

Hard skills refer to your technical ability – the hands-on skills that show you know how to build, test, and ship software. These are often the first things employers check on your CV or GitHub profile.

With cloud adoption, DevOps culture and AI tooling now part of many engineering teams, employers are looking for candidates with practical knowledge of today’s most-used tools and platforms.

Let’s start with the programming languages and tools every software engineer should be familiar with in 2025.

Programming and languages

Programming is the core of software engineering, but it’s no longer just about knowing how to write code. Employers now want engineers who can write clean, efficient code, understand version control, and work with frameworks across front-end, back-end and full-stack environments.

JavaScript

JavaScript remains essential, especially for front-end and full-stack developers. It’s the foundation of many modern web frameworks like React, Vue, and Node.js, and is widely used across startups and enterprise teams alike.

Being comfortable with JavaScript also means understanding asynchronous programming, DOM manipulation, and browser APIs. If you’re aiming for a product-focused role or want to work on scalable web applications, strong JavaScript skills will open doors.

Python

Python’s flexibility makes it a must-have for software engineers in 2025. It’s used in everything from scripting and automation to machine learning, data engineering, and backend web development.

Its popularity is fuelled by frameworks like Django and Flask, and its growing use in AI, data science, and DevOps workflows. Python is also beginner-friendly, which means employers often look for it as a base skill even in more senior roles.

If you’re applying for software roles that overlap with AI, cloud, or scripting-heavy environments, Python will likely be a key requirement.

TypeScript

TypeScript builds on JavaScript by adding static typing. This makes it easier to manage complex codebases and reduce bugs, especially in large front-end applications.

Many modern companies now default to TypeScript over JavaScript in their front-end and full-stack projects. Hiring managers often see it as a sign of scalable thinking and code reliability.

Learning TypeScript is a smart move if you're applying for roles that involve React, Angular, or enterprise-level front-end applications.

SQL & PostgreSQL

SQL has been around for decades, but it’s still one of the most requested software engineering skills in job descriptions. Knowing how to query relational databases is essential for back-end developers, data engineers, and full-stack roles.

PostgreSQL is one of the most popular databases in 2025 because of its performance, reliability, and support for modern features like JSON, full-text search, and extensions.

Knowing how to write optimised SQL queries, manage schemas, and work with production-level PostgreSQL databases is often seen as a practical strength by engineering teams.

Development tools & version control

Today’s software engineers are expected to be confident using version control, automation pipelines and development tools that support collaboration and code quality. These skills are no longer seen as a nice-to-have. They’re essential in almost every modern engineering environment.

From Git to CI/CD pipelines and testing frameworks, hiring managers want to see that you understand how software is built, tested and deployed in the real world.

Git & GitHub

Git is the standard version control tool used across software teams. GitHub is where collaboration happens. Whether you're building features, fixing bugs or reviewing someone else’s code, knowing how to work with branches, pull requests and commits is expected.

But it’s not just about knowing commands. Employers also want to see that you understand best practices. Writing clear commit messages, contributing to code reviews and handling merge conflicts are key parts of the role. If you can showcase projects on GitHub or contribute to open source, that will boost your profile.

Continuous integration / Continuous deployment (CI/CD)

CI/CD is now widely used to automate build, test and deployment processes. This helps teams ship code faster and more reliably by catching issues early and reducing manual work.

You don’t need to build pipelines from scratch, but you should understand how they work and how to troubleshoot when something fails. Tools like GitHub Actions, Jenkins and CircleCI are common. If you’ve worked in a team that uses CI/CD, highlight this in your CV or portfolio to show you're familiar with modern workflows.

Testing frameworks (Jest, PyTest, etc.)

Writing tests is a core part of being a reliable developer. Whether you use Jest, PyTest or another framework, having experience with automated testing shows that you write code that works and is easy to maintain.

Jest is popular for JavaScript and React-based projects. PyTest is a common choice in Python. You don’t need 100% coverage, but writing unit and integration tests and following test-driven development principles when appropriate are signs of quality engineering.

Testing also shows that you think ahead. It means you're not just writing code for today, but for the team that will maintain it tomorrow.

Cloud & DevOps skills

Cloud platforms have become part of the everyday toolkit for software engineers. Whether you're deploying a web app, processing data or scaling a service, cloud skills are now part of the job. Alongside this, DevOps practices like automation and infrastructure management are becoming more common in development teams.

Even if you’re not a cloud or DevOps specialist, having a working understanding of these areas makes you more valuable to employers.

AWS / GCP / Azure basics

Most teams work with at least one of the main cloud platforms. Amazon Web Services (AWS), Google Cloud (GCP) and Microsoft Azure each offer tools and services for deploying and managing applications.

You don’t need to master all three. But knowing how to set up compute resources, store data securely or configure basic networking will give you an advantage. If you’ve used serverless functions or managed services like Firestore or DynamoDB, include those too. It’s not about being a cloud engineer. It’s about being able to work in cloud-native environments with confidence.

Docker

Docker allows you to create containers that bundle up your code, dependencies and environment. This makes your applications more portable and easier to deploy across different machines or environments.

For many engineering roles, Docker is expected knowledge. You should understand how to write a Dockerfile, build an image and run containers locally. If your project needs to run consistently in different environments, Docker helps ensure that what works on your machine also works in production.

Kubernetes

Kubernetes helps manage and scale containers in production. It’s commonly used in larger systems and cloud-native architectures. While not every engineer needs deep Kubernetes knowledge, understanding the basics is useful.

Being able to describe what Kubernetes does, and how it handles scaling, load balancing or failover, shows employers that you’re ready to work in environments where applications are deployed and scaled automatically. Even if you won’t use it every day, it’s a valuable skill to bring to the table.

Infrastructure as code (Terraform, Pulumi)

Infrastructure as code lets you manage cloud infrastructure using configuration files rather than manual setup. Tools like Terraform and Pulumi allow you to create repeatable environments that can be version-controlled and reviewed like application code.

This approach is widely used in DevOps, platform engineering and larger development teams. If you’ve deployed infrastructure this way, even at a basic level, it shows that you understand how software systems are built from the ground up — not just the application layer.

AI & emerging tech

AI isn’t just a trend. It’s already changing the way software engineers write, test and deploy code. From AI-assisted development to machine learning integration, employers now want engineers who understand how these tools fit into real-world workflows.

Staying current with AI and emerging tech shows you're thinking ahead. Even if you’re not an AI specialist, having exposure to these technologies can make you a stronger candidate for a wide range of roles.

GitHub Copilot / AI pair programming

GitHub Copilot is one of the most visible AI tools in software development today. It suggests code, completes functions and even writes tests based on your context. While it doesn’t replace developers, it does improve speed and productivity.

Knowing how to work with Copilot effectively is increasingly expected in some teams. It’s less about relying on the tool and more about knowing how to review, refine and validate what it produces. Employers see this as a practical skill that can boost performance without sacrificing code quality.

Using Copilot in your projects  and mentioning it in your CV or portfolio,  shows you're open to using AI in a responsible and productive way.

Prompt engineering

Prompt engineering is becoming a valuable skill for software engineers working with AI tools, APIs and LLMs (large language models). It’s all about knowing how to ask the right questions or give the right context to get useful results from AI systems.

For example, if you're building a chatbot, writing a script or automating a process, the way you structure prompts can have a big impact on the outcome. Prompt engineering is also helpful when working with tools like ChatGPT, Bard or Claude in development tasks.

Having this skill shows you can use AI tools intelligently and can troubleshoot when the output isn’t quite right. That’s something employers are starting to value more, especially in AI-enabled workplaces.

Integrating LLMs / APIs

More companies are integrating large language models (LLMs) into their products. That means engineers are now expected to understand how to connect with these models through APIs and manage responses safely and effectively.

Knowing how to send and handle API requests, structure output and manage costs or rate limits is part of this. You might work with OpenAI, Anthropic or open-source models depending on the business. This is especially useful in product, SaaS or data-driven environments where AI is now part of the core experience.

If you’ve experimented with integrating APIs like OpenAI’s GPT-4 or used them in production, include that in your CV or GitHub profile to highlight practical experience.

MLOps & model deployment basics

Machine Learning Operations (MLOps) is where engineering and data science meet. Even if you’re not building models yourself, it’s helpful to understand how they’re deployed, tested and monitored in production.

MLOps includes versioning models, tracking experiments and using tools like MLflow, SageMaker or Vertex AI. If you’re aiming for roles that overlap with data or AI, knowing how ML models are trained, deployed and maintained will set you apart.

This knowledge is also important when working with teams that use machine learning in their product or service, even if you’re not leading that part of the stack.

Security and risk mitigation

Security is no longer just the responsibility of dedicated security teams. Software engineers are now expected to consider security at every stage of development. With supply chain threats, data breaches and regulatory pressure on the rise, hiring managers want to see that you understand how to build secure systems from day one.

Whether you’re writing backend services or working with APIs, having a strong grasp of secure coding and risk awareness can help you stand out and build more resilient software.

Secure coding practices

Secure coding is about writing software that minimises vulnerabilities. It means validating user input, avoiding hard coded secrets, handling errors carefully and being aware of common attack vectors like cross-site scripting (XSS) or SQL injection.

Employers want engineers who take responsibility for code safety, especially if you’re working on customer-facing apps or handling sensitive data. Following best practices from OWASP and using tools to identify vulnerabilities early in the development process are signs of a thoughtful and dependable developer.

You don’t need to be a security expert. But having a mindset that puts safety first shows that you care about the integrity and trustworthiness of your code.

Threat modelling

Threat modelling helps identify where and how your system could be exploited. It’s a way of thinking ahead by asking questions like: What are the assets? What are the threats? Where are the vulnerabilities?

Being involved in threat modelling shows that you can anticipate problems before they occur. Even basic familiarity with tools like STRIDE or DFDs (Data Flow Diagrams) can be useful in interviews and team discussions.

If you’ve taken part in any threat modelling workshops or sessions, it’s worth including that on your CV. It’s a skill that is increasingly valued in teams where developers take shared ownership of system quality and resilience.

DevSecOps mindset

DevSecOps stands for development, security and operations. It’s about embedding security into your development workflow, rather than treating it as something separate or last-minute.

A DevSecOps mindset means you’re thinking about security at every stage, from code commits and build pipelines to deployment and monitoring. It also means using tools like static analysis (SAST), dynamic testing (DAST) and dependency scanners to catch problems early.

Companies adopting DevSecOps want developers who work well across functions and understand how security supports the business, not just compliance. Showing that you’ve worked in a DevSecOps environment or understand the principles can be a strong signal to employers.

Supply chain security tools

Modern software projects often depend on dozens or hundreds of external packages. These packages can introduce vulnerabilities, even if your own code is clean. Supply chain security focuses on identifying and reducing this risk.

Tools like Dependabot, Snyk or Renovate are used to keep dependencies up to date and check for known vulnerabilities. Understanding how to manage dependencies, check changelogs and spot red flags helps protect your applications and your users.

In 2025, software engineers are expected to have some awareness of supply chain risk. If you’ve worked in a team that actively manages this, or if you’ve used automated tools to keep dependencies secure, be sure to include it in your project experience.

Core engineering concepts

Strong software engineers don’t just know the tools — they understand the underlying concepts that make code efficient, scalable and maintainable. These fundamentals form the basis of most technical interviews and are used daily in real-world engineering environments.

Employers value candidates who can reason through design decisions, solve technical problems methodically and communicate how systems are built. Understanding the core principles helps you work across teams, stacks and project types.

Object-oriented programming (OOP)

Object-oriented programming is a foundational concept in software engineering. It focuses on structuring code around objects, which combine data and behaviour. Languages like Java, Python and TypeScript all support OOP principles such as encapsulation, inheritance and polymorphism.

Understanding OOP helps you write modular code that is easier to test, debug and extend. Many companies rely on object-oriented design patterns to build reusable components and scalable systems. It’s also commonly assessed in technical interviews, especially for backend or full-stack roles.

If you’re aiming to level up, go beyond knowing the terms. Practise applying OOP principles in your own projects and be ready to explain why they matter.

REST / GraphQL APIs

APIs are essential for connecting systems, sharing data and building scalable web applications. REST is the most common style, known for its simplicity and use of HTTP methods. GraphQL is a newer alternative that allows clients to request exactly the data they need.

Knowing how to design and consume APIs is a must-have skill for most engineering roles. Employers want developers who can handle API authentication, versioning and error handling, and who understand how front-end and back-end systems communicate.

If you’ve built or worked with APIs, show this in your project work. Include examples of API calls, documentation or tools you’ve used such as Postman or Swagger.

Microservices architecture

Microservices break an application into smaller, independent services that communicate over a network. This makes systems easier to scale and maintain but also introduces complexity in terms of deployment, communication and monitoring.

Understanding microservices shows that you can think at a systems level. You should know the basics of service discovery, API gateways and how services are deployed and managed. Concepts like eventual consistency, service resilience and observability often come into play.

If you’ve worked on projects that use microservices — even partially — explain your role and what you learned. Companies working at scale will often prioritise candidates with this kind of experience.

Database management & query optimisation

Almost every application relies on a database, and engineers are expected to know how to design, query and maintain them. This includes normalisation, indexing, transactions and knowing when to use SQL vs NoSQL solutions.

Optimising queries is just as important as writing them. Employers want to know that you understand performance basics — avoiding full table scans, using indexes wisely and managing data relationships effectively.

Experience with tools like PostgreSQL, MySQL, MongoDB or Redis is often requested in job specs. If you’ve solved performance issues, improved database design or implemented backup and recovery processes, these are worth highlighting when applying for software engineering roles.

Soft skills for a software engineer

Technical skills may get your foot in the door, but it’s often soft skills that help you grow and succeed in a software engineering role. In 2025, employers are putting more focus on how developers collaborate, communicate and adapt within their teams.

Being technically strong is no longer enough. Software engineers now work closely with designers, product managers and other stakeholders, so your ability to explain ideas, take feedback and solve problems together can make a real difference to your career progression.

Below are the key soft skills that will support your technical ability and help you succeed in the workplace.

Communication

Clear communication is one of the most important soft skills for software engineers. Whether you're explaining technical details to non-technical colleagues or writing documentation, how you communicate affects how your work is understood and valued.

Strong communication skills help you work better in teams, speed up problem-solving and reduce confusion during development. It’s also a key skill in interviews and code reviews.

Practise explaining your code and decisions out loud. The ability to keep things clear, simple and accurate is highly valued by hiring managers.

Team collaboration

Modern software development is a team effort. Engineers rarely work in isolation, especially on production systems. Whether you’re working with front-end developers, designers or stakeholders, being collaborative makes the work smoother and faster.

Good collaboration means listening, sharing knowledge, supporting your team and being open to other people’s ideas. It helps build a culture of trust and accountability. Teams that collaborate well tend to ship better software and enjoy the process more.

If you’ve worked in agile or cross-functional teams, talk about what you contributed and how you worked with others to achieve shared goals.

Critical thinking & problem solving

Software engineering often involves working with incomplete information and solving problems that don't have a clear answer. That’s where critical thinking comes in.

Employers look for engineers who can break down complex issues, evaluate options and make decisions that are both practical and scalable. Whether it’s debugging a tricky error or designing a new feature, the ability to reason through problems logically is a core part of the role.

Problem-solving also means knowing when to ask for help and how to search for the right solution. It’s a skill you can keep developing throughout your career.

Adaptability

Technology changes quickly. So do priorities, teams and business needs. Being adaptable means you can keep up, stay calm when plans change and learn new tools or systems as needed.

Employers want engineers who don’t get stuck or overwhelmed when things shift. Whether it's moving from one codebase to another or adjusting your approach based on feedback, adaptability helps you stay productive and positive.

You don’t need to know everything right away, but being open to learning and change shows you're a reliable part of any tech team.

Attention to detail

In software development, small mistakes can have big consequences. That’s why attention to detail matters. Whether you're reviewing a pull request, writing tests or checking your own code, catching small issues early helps maintain quality.

Engineers with strong attention to detail spot inconsistencies, fix problems before they reach production and write better documentation. These skills build trust with colleagues and reduce the time spent on rework.

If you’re applying for roles where quality and stability are key, showing that you take pride in the details can help you stand out.

Time management

Time management helps you balance competing priorities, meet deadlines and keep projects moving forward. In agile teams or sprint cycles, being able to estimate work accurately and deliver on time is critical.

Employers value engineers who can manage their workload independently, communicate if timelines need to shift and keep things on track without constant supervision.

Good time management also shows that you respect your team’s time and the goals of the wider business.

Self-organisation in agile teams

Agile working requires a high level of self-organisation. There are often no rigid instructions or micromanagement. Engineers are expected to manage their own tasks, contribute during stand-ups and work collaboratively during sprint cycles.

Self-organisation includes things like picking up tickets proactively, updating your progress clearly and completing work to a high standard. It also means giving and receiving feedback constructively.

If you’ve worked in agile or scrum environments, highlight how you’ve contributed to delivery and team rituals like retros or planning sessions. Employers want to know that you can manage your own work and support the success of the team.

How to improve software engineering skills

Whether you're just starting out or already have a few years of experience, there’s always room to grow as a software engineer. The best candidates are those who take learning seriously and treat their skills as something that can always be improved.

In this section, we’ll look at simple, effective ways you can develop both hard and soft skills. These actions are based on what we see working across hiring processes every day, and what employers tell us they value in real-world candidates.

Master AI-powered coding workflows

AI is changing how engineers write and ship code. Learning how to use AI tools like GitHub Copilot or ChatGPT to assist with repetitive tasks or generate boilerplate code can make you more efficient and free up time for more strategic thinking.

But it’s not just about speed. Knowing how to guide these tools properly, check the outputs carefully and integrate them into your workflow is becoming a sought-after skill. Employers want engineers who can use AI as a support tool without becoming over-reliant.

If you can show that you use AI to improve your work, not replace your thinking, that puts you in a strong position in 2025.

Earn cloud-native & Kubernetes credentials

Certifications are a great way to build credibility, especially in cloud and DevOps environments. Courses from AWS, Microsoft Azure or Google Cloud show employers that you understand how to build and deploy in real-world cloud systems.

If you're working towards roles in infrastructure or backend development, learning Kubernetes is also worth the effort. Courses from providers like the CNCF (Cloud Native Computing Foundation) give you a foundation in container orchestration, which is used across many large tech environments.

You don’t need a long list of certifications, but one or two relevant ones can give your CV a big lift.

Build projects & GitHub activity

Real-world experience speaks louder than theory. Building your own projects and sharing them on GitHub is a great way to show what you’ve learned and how you apply your skills.

Whether it’s a side project, an API, a portfolio site or a script that solves a problem, the goal is to demonstrate initiative and practical ability. This also gives you something concrete to show in interviews, beyond qualifications or course certificates.

Make sure your GitHub is active, organised and includes a few short descriptions. Hiring managers often check GitHub as part of the shortlisting process.

Contribute meaningfully to open source

Contributing to open source is one of the best ways to learn how to collaborate, review code and follow professional standards. You don’t have to fix major bugs or build big features. Even small pull requests, code clean-ups or improvements to documentation can help you get started.

Look for beginner-friendly issues or projects that match your interests. Platforms like GitHub and GitLab make it easy to browse open projects. By contributing, you’ll build both your skills and your reputation in the developer community.

It also shows potential employers that you take initiative and can work within a team-based environment.

Build a feedback & mentorship loop

Getting feedback is one of the fastest ways to grow as a developer. That could mean code reviews from peers, advice from a more experienced engineer or working with a mentor who helps guide your development.

You don’t need a formal mentorship programme. Even asking for feedback on a project or pair programming with someone more senior can make a big difference. Learning from others helps you see blind spots and strengthens both technical and soft skills.

If you’re not already doing this, look for ways to build feedback into your weekly routine.

The most successful software engineers in 2025 will be those who combine strong technical skills with solid communication, collaboration and problem-solving.

At Digital Waffle, we help software engineers find roles that match their skillset and support their growth. We know what employers are looking for and can help you position yourself for the next step.

Looking for your next opportunity? Browse our latest software engineering jobs. Want to get in front of the right employers? Submit your CV and one of our consultants will be in touch to help you take the next step.