What Tech Stack should you target for a Job Search?

Hi everyone, it has been a while since we wrote these types of posts in the development category. We started a Tutorial series about ReactJS where we started from beginning to end with complete theoretical as well practical knowledge, but that’s just a start. We though this might be worth sharing now, as many people are currently looking for a job. As this is the time for new Students joining education institutions as well. So, this guide will help both freshers as well experienced developers for deciding a career they want to go, basically the tech stack to choose. Let’s discuss about Tech Stacks you can choose.

Intro to Tech Stack

You might be wondering what a tech stack is, so here let us explain. A tech stack refers to the combination of technologies, programming languages, frameworks, and tools used to build a software application. It’s like the foundation and building blocks of a software project.

Let say a Tech Stack is a proper meal with everything from Rice, Bread, Vegetable, Sweet dish we need to eat to make it a complete project. I know it’s a foodie example but let take another example. While building a house, there are different things to do like Planning the architecture, building the base and rooms, designing the rooms, adding electric components lights and plumbing with furniture. If a person, provides these whole services in a single contract then we can say these services combined is a Stack of services he provides.

So, what we mean to say is A Tech stack basically contains of multiple things if we talk about Software.

Key components of a tech stack

There are multiple key components of a tech stack, so here is a categorized list of things in a stack that makes the full web application or basically software development done.

Frontend

Frontend technologies are used to create the user interface (UI) that users interact with. Examples include HTML, CSS, JavaScript, and frontend frameworks like React, Angular, or Vue.js. This is the part where the designers work on things like animation, styling, graphics and more.

Backend

Backend technologies are used to handle server-side logic, data storage, and application functionality. Examples include programming languages like Python, Java, or Node.js, and frameworks like Django, Spring Boot, or Express.js. Backend basically contains the APIs, Configuration, Database connections, and storage related logic. It also handles the user authorization and security.

Database

Database technologies are ones used for storing and organizing data, indexing and searching data. Examples include relational databases like MySQL, PostgreSQL, or Oracle, and NoSQL databases like MongoDB, Redis, or Cassandra. Other than NoSQL, and SQL Databases, we do have search based databases like Elasticsearch for making efficient and fast searches in combination with SQL/NoSQL databases for efficient and secure storage. The Databases can be disk based, Dockerised or Self hosted by Database providers using APIs only.

Cloud Platform

A cloud computing service that provides infrastructure, platform, or software as a service. Examples include AWS, GCP, or Azure. Cloud or Servers generally we say, are used to host the application code, Deploy services, applications and more. Cloud platforms as well provide software services and integrations that we use to add functionality to our application.

For example, S3 Buckets from AWS for Object Storage, Google Maps integration from GCP, Gemini API for adding AI services, and GPT API for adding AI with ChatGPT support. Having knowledge of Cloud is required for DevOps work.

DevOps

DevOps stack is basically the collection of tools used for deployment, testing, automation for software development process. DevOps work usually starts from the beginning of a new project, with the process of creating a CICD pipeline that

• Gets code from the git with a webhook and triggers the pipeline
• Runs testing and quality check with services like SonarQube
• Publishing reports and deployment analytics
• Replacing Production (Live) Code with updated code and informing any mail recipients

The whole process is critical and helps companies to manage applications deployment easier, to let customers enjoy new features as soon as possible. Automation once done, does not need any work but only when there are errors or update required with commands/services for updated code. DevOps also helps Developers to test and deploy their code, thus DevOps and Development is connected.

Example of DevOps stack tools include Jenkins, GitHub CICD pipeline, Circle CI, Chef, Puppet and more. Now a days new services like Infrastructure as a Code also comes under DevOps. Examples are like Terraform, Ansible, AWS Lambda, AWS amplify.

There are also containerization technologies that makes deployments, Docker and Kubernetes. Docker is Open source and recommended for smaller projects, whereas Kubernetes are more professional and for High Traffic sites and complex projects, and for companies with Investments as requires more resources than Dockers.

Full Stack vs Normal Developers

Full Stack Developers are the ones who are expert in Both the Frontend as well as the backend, which is client side as well the server side, of a Web application. While the Tech Stack is different based on the requirements in a company and projects, the core responsibilities and skills are generally similar as both do the same work. But Full Stack can work on more areas of a web application as well different tech stacks.

Skills and areas common for both full stack and Normal Developer

• Programming languages: Both full-stack and normal developers typically use languages like JavaScript, Python, or Java.
• Problem-solving: The ability to break down complex problems into smaller, manageable tasks is essential for both roles.
• Debugging: Both roles involve identifying and fixing errors in code.

How full-stack developers differ from normal developers:

• Breadth of knowledge: Full-stack developers have a broader understanding of the entire application stack, from the frontend to the backend. This helps to identify issues in connectivity between frontend and the backend. Can also help both Backend and Frontend Devs.
• Versatility: They can work on different parts of a project as needed, making them valuable assets to development teams. Examples are API Development, UI Design, Code Configuration, Integrations and more.
• Communication skills: Full-stack developers often need to communicate effectively with both frontend and backend teams, requiring strong interpersonal skills.
• System-level understanding: They have a better understanding of how different components of an application interact, allowing them to make informed decisions about design and architecture.

Full-Stack with DevOps

A Full-Stack Developer with DevOps skills combines the traditional full-stack responsibilities with expertise in DevOps practices. This involves understanding and implementing tools and processes that automate the software development lifecycle, from development to deployment and operations. In short if a Full stack is a gold, then Full Stack with DevOps is a diamond. Also, Full stack Devs are rare, and the Full Stack with DevOps are rarer.

Key areas of expertise for a Full-Stack Developer with DevOps:

• CI/CD pipelines: Building and maintaining automated pipelines for continuous integration and continuous delivery.
• Infrastructure as Code (IaC): Using tools like Terraform or Ansible to manage infrastructure resources.
• Containerization: Understanding and using Docker or similar technologies to package applications.
• Cloud platforms: Familiarity with cloud providers like AWS, GCP, or Azure.
• Monitoring and logging: Implementing tools to track application performance and identify issues.

Benefits of a Full-Stack Developer with DevOps:

• Increased efficiency: Automation of tasks leads to faster development and deployment cycles.
• Improved reliability: Consistent and predictable deployments reduce downtime.
• Enhanced scalability: Easier to handle growing user demand.
• Better collaboration: Strong understanding of the entire development process fosters better teamwork.

In essence, a Full-Stack Developer with DevOps skills is a versatile professional who can contribute to both the development and operations aspects of a software project, making them a valuable asset in modern development teams.

Choosing the right tech stack

There is not one fit Tech Stack for all needs, so it differs for each organization based on the usage and requirements, plus the level of skills needed. For example, for Data Analysis, we need to use Python because there are multiple libraries available to easily achieve those tasks. For working with AI/ML projects as well, Python is used because of libraries available like NumPy, Keras, Pandas, TensorFlow and more.

On the other hand, for creating static sites with limited information, A simple React app can be sufficient. For use with ecommerce products, and large user base, Java can be better in handling things and server load coupled with React/Angular based Frontend for SPA applications.

So, let’s see a few tech stacks based on the areas of development

Frontend Development

For frontend, mainly we recommend JavaScript based frameworks because of the popularity and simplicity. JavaScript is also used in some Backend frameworks as well with some limitations, though.

• Angular: A full-featured JavaScript framework for building complex web applications. Angular was launched around 2016 and was the loved framework because of the backing of the Google. So, multiple MNCs still use Angular Framework for managing old projects.
• React: Another popular JavaScript library for building user interfaces and backed by Facebook. React is also SPA, but with less code than Angular required for same development. It gained more users than Angular and is used for modern projects. So, more companies building is preferring React over Angular.
• Vue.js is a progressive JavaScript framework for building user interfaces. It’s known for its flexibility, simplicity, and large ecosystem.
• Nuxt.js is a higher-level framework built on top of Vue.js. It provides a set of conventions and tools that simplify the development of server-side rendered (SSR) Vue.js applications. Nuxt.js offers features like automatic routing, data fetching, and performance optimization.

Backend Development

For most of the projects, older as well mid age, there is Java based backend because of the features provided by Java and performance. But small scale projects, as well some large projects, are using Nodejs because of benefits of JavaScript.

• Java (Spring Boot): A versatile language for building enterprise-scale applications. Frameworks like Spring Boot are mostly used in big companies for creating high load applications for industries like Ecommerce, Finance and Health. Maven and Gradle are used to manage dependencies.
• Python (Django/Flask): A popular language for web development, with frameworks like Django and Flask. Same as Java but used more for AI and ML projects where analysis is done. Such as Face Recognition, pattern analysis, Medical and Data analytics usage. For speech recognition usage. So, Python is used for special projects only. Use of PIP libraries and wheels for dependency with virtual environment.
• Node.js: A JavaScript runtime environment for building server-side applications. Best for JavaScript developers, so one person can work on both frontend as well as backend. Popular because of JavaScript Libraries support available with NPM registry. Used for small scale as well Hobby projects. Used by startups to create simple projects, that don’t require anything from Java/Python both.

Most of the newcomer prefer NodeJS because of simple learning curve over Python that requires specialization. Some say Java is dead, so they don’t use Java, but in reality, Java is now more optimized for large scale projects only and to meet the needs of specific companies. Thats why people avoid Java for smaller projects. Another reason can be because of the learning curve of two languages, one Java, one JavaScript, over just using one JavaScript for both.

Full-Stack Development

We talked of things as separate before but now let’s talk of Full Stack development. Let say, me specifically being a Full Stack have worked wearing multiple hats over a specific time, during working in startups. So, I can say, Full Stack development is for ones that loves to learn multiple things and explore to expand their career. But sometimes at a point, one can decide to make a career in one tech or switch tech, so both are fine. No tech or stack is fixed, and a person should be able to change freely on his own will, so that he can enjoy what he does.

Some popular stacks you can see below:

• MERN Stack: MongoDB, Express.js, React, Node.js
• MEAN Stack: MongoDB, Express.js, Angular, Node.js
• LAMP Stack: Linux, Apache, MySQL, PHP

Here the MERN, and MEAN stack are both popular and multiple companies use these stacks, but MERN stack is the futureproof as more are moving towards React based frameworks like Svelte, NextJS etc.

One issue that most of the face being Full Stack working for companies is that sometimes, in a company there is not much work for a single tech, so you work on multiple things as per need. This is why with experience of let say 3 years in a startup, you might not have 3 years exp of Python/Java alone, but a mixed things and companies sometimes only need full experience for a specific skill. This is why one need to make sure, to at least pick and work on one technology, even if you do multiple techs just to have required experience for a specific role.

A Tip, if you are in similar job, then you can do create projects on your own and gain knowledge, then you can easily answer the questions, if asked to justify the experience. That way, you can freely say, you have 2 years exp in X tech.

Mobile Development

This is for a specific purpose only as the target is mobile application. We can do both Native and Hybrid development, but companies prefer Native for performance vs Hybrid for faster development.

• iOS (Swift/Objective-C): For developing native iOS applications.
• Android (Kotlin/Java): For developing native Android applications.
• React Native: A framework for building cross-platform mobile apps.
• Ionic – Hybrid apps with React/Angular based framework for building web based mobile apps.
• Capacitor – It’s a new and modern web-based UI Components framework, can be used along with Ionic or independently. It is not native but provide near to Native performance with old school JavaScript.

So, why Native and Hybrid, simply because Native tech is built specifically for mobile and they provide better performance for application development. On the other hand, Hybrid apps are meant for Web Developers who don’t want to learn a tech just for building mobile apps.

Hybrid apps use kind of hack to interact with Native libraries after final build, so they can be efficient based on how close the native code it uses.

So, companies with enough money and no budget issues, prefer native development with Swift/Kotlin/Java for mobile apps. And companies with low funds, and with more web devs prefer Hybrid apps.

One noticeable benefit of Hybrid apps is the code reusability, and less time to ship. Because they are already Web based, one can implement same logic with similar functionality in the Hybrid app easily without any extra work. This makes development of Hybrid apps easier and beneficial, as well making users get their hands on the new features fast.

On the other hand, Native apps can be delayed because of issues with tech logic not available in the native code vs the web code. So, development can be complex and takes time in most of the cases. Thats why for some products, we don’t see all the features available on the web, in the mobile version of the same product.

So now you also if you complain why this feature not yet in the mobile application, then you need to know and understand that it’s not easy to do that and might be impossible in some cases because of the native development issues.

Data Science and Machine Learning

The very popular and new trend, Data Analytics that is making everyone to go for it. Specially the new students, who are targeting to enter the industry. With many years of data gathering, and everything almost connected with apps. We have a lot of data, that need to be processed. So, companies needing specialized engineers that are known as Data Scientists are required. Data Science also require some specialized tools only and have a learning curve to it. It also requires the knowledge and love for Maths as you deal with Statistics and calculations.

• Python (Pandas, NumPy, Scikit-learn, TensorFlow): A popular language for data science and machine learning. You can use it for anything from training a LLM(Large Language Model), deep speech model, Pattern recognition, Face recognition, Intelligent systems and more.
• R: Another popular language for statistical analysis and data visualization.

Apart from analytics machine learning includes creating specialized chatbots for customer service, banking, report generation, risks identification and more. In modern healthcare, Python tech is used to create models that can recognize diseases in early stages and can also help with the treatment.

Programming smart devices like Arduino, Raspberry, smart boards, sensors all make use of Python Tech mostly.

Cloud Computing

Cloud Computing stack includes things like Hosting, Database, Managed services provided by Cloud Providers like:

• AWS (Amazon Web Services): A comprehensive cloud platform with service based APIs and SDKs for reading text, text to speech, pattern recognition, data storage, and more.
• GCP (Google Cloud Platform): A cloud platform with a focus on data analytics and machine learning. Provides services like training Large Language models with open source data set and tools available to developers. also providing similar services as AWS.
• Azure: A cloud platform from Microsoft similar to above two, but comparatively less popular.

Cloud computing stack basically is related to Hosting companies as well SAAS(Software as a service) providing managed Database as well softwares like Data Dog for analytics.

DevOps

The one stack where it’s not about coding, but scripting. What we means is one don’t do whole code under this stack, but small scripts to execute a specific task(s). It can be a testing related task, monitoring the application availability, or creating timely backups. Everything makes use of DevOps stack. Let us see some tools:

• Ansible: A configuration management tool to create scripts for OS based tasks, even multiple tasks at once easily. example be like installing a same application on 100 servers at a time.
• Terraform: It is a popular infrastructure as code (IaC) tool used to define and provision infrastructure resources like servers, networks, and storage. It uses a declarative language (HCL) to describe the desired state of the infrastructure, and Terraform automates the process of creating, modifying, and destroying these resources.
• Jenkins: A continuous integration and continuous delivery tool to automate deployment of application with git webhooks.

So, you can choose from the above listed Stacks as a deciding factor for what you want to choose to make a career. Let us also see What stacks are popular with the companies.

Popular Stacks or Technologies Companies using

We discussed a lot of different classifications for deciding the stack. Now let us discuss a few popular stacks that companies might be using.

• Angular/Spring Boot/Postgres
• React/NodeJS/Docker/MongoDb
• Python/MySql
• Python/AI-ML/Analytics
• React/Java/Spring Boot
• Nodejs/Angular

For frontend companies prefer React/Angular, with Spring Boot/Nodejs as Backend. PostgreSQL for relational Database and MongoDB for NoSQL database. They might also need Docker for containerization or Kubernetes.

Data analytics and AI related companies use Python/MongoDB for performance stacks.

Some Deciding Factors

• Older companies still use Angular with Java
• Newer companies with existing projects are using React/Nodejs
• Older as well newer companies for new projects using React/NextJS with MongoDB/PostgreSQL.

Targeting Company

Also based on the company size, you should decide which company to target, so you have expected work and skills accordingly.

• Startups: Smaller companies, often looking for versatile developers with a willingness to wear multiple hats. So mostly Full Stack or Full Stack with DevOps roles are mostly hired for. For freshers looking to gain experience or people with at least 2-3 years exp.
• Mid-sized Companies: Established companies with growing teams, seeking experienced developers with specific skill sets. Full Stack or normal developers preferred with two skills like Java, and Angular or React. You can target if you have 4-5 years of experience. Freshers may also be required with provided training.
• Large Corporations: Mature organizations with well-defined roles and processes, requiring specialized expertise. They require more experience and specialization so roles may be only Java, Python, React, or only DevOps. You need to target only if you have more than 7-8 years of experience.

Some Interview Preparation Tips

The hiring process is different for each company, so you need to prepare differently for each company. Some companies require you to have DSA knowledge, but if you don’t like DSA, then don’t worry, you can filter out those companies by checking if they require Hacker Rank, Leet Code or any other coding platform. let’s check tips:

• Technical Questions: You need to practice coding challenges, algorithm design, and data structures to get selected in top MAANG companies as well Big 4 Companies.
• Behavioral Questions: Prepare answers to questions about your past experiences, problem-solving skills, and team collaboration. This is required in most of the client facing roles.
• System Design Questions: Understand how to design large-scale systems, considering scalability, performance, and reliability. This is required for Live projects with large user base companies like Amazon, Facebook.
• Mock Interviews: Practice with a friend or mentor to simulate real interview scenarios. You can also use AI interview platforms to practice interviews. Platforms like Naukri do provide this service.
• Questionnaire – One secret that no one knows and tell, is interviewers also use same platforms to ask questions. Search for top interview questions, to prepare for theoretical questions. Be creative in answering those questions.

Bonus Tips

Some additional information for you

• Networking: Connect with industry professionals on LinkedIn and attend tech events. Networking is the key to get some jobs that are not even listed on the Job Boards. Now a days, companies like to hire in person without going through long hiring process. So make sure to attend events, you can also get free TShirt and goodies.
• Online Courses: Platforms like Coursera, Udemy, and edX offer courses to enhance your skills. They provide paid courses, but if you don’t want to spend money, then you can also learn from YouTube Channels like Code.org, Code with Harry, Free Code Camp and many more. You can also practice with coding projects
• Personal Projects: Build personal projects to showcase your abilities and learn new technologies. It’s the best way to learn coding and believe us you don’t even need to have a college degree to start. Many companies hire directly without any degree, if you are skilled in what you do. So this is for non tech people, go ahead and get a software job, be free from sales.
• Stay Updated: Keep up with the latest trends and technologies in the software development industry. You can read programming blogs on platforms like Medium, Dev.to, Hashnode to keep you updated on technology as well programming tips.

Summary

So, we explored about different Tech Stacks, their usage and how companies are using. We also explained what the technologies are and how to categorize them. That must be enough for you to understand Tech Stack now and get a job. We still have so much to cover in this post, but we could not, so we will be writing another post related to interview preparation, required skills, and choosing companies.