A 5-Level Pyramid to Becoming a Software Engineer in 2025
If one wanted to become a software engineer in 2025, this is everything they should do. In this article, we will reveal the five-level pyramid to becoming a software engineer. You have to go in order because each level builds on the previous one, and it gets smaller as we go up because it gets more challenging. There are only a few people who can get to the top properly. So, I hope you're ready to take your career to the next level. With that being said, let's get started right away.
Level 1: Master the Fundamentals of Code
Coming in at level one is learning how to code, but this is where many people make a huge mistake: they fall into tutorial hell. This is what happens when you spend all your time watching endless coding tutorials, thinking you're learning, but you're not actually building anything or solving problems. If all you do is watch motivational, productive TED talks but you don't do anything differently, you haven't learned anything. Especially coding—it's not like biology or psychology where you mainly memorize vocabulary terms. You actually have to shift your mindset, roll up your sleeves, and become a problem solver.
You do that by following the "build to code" framework. Here's how it goes.
First, start by learning some foundational computing concepts just to get your feet wet and establish your mindset. Consider taking the CS50 course by Harvard. It's beginner-friendly and completely free. It covers topics like algorithms, data structures, and computer architecture. It gives you theory with hands-on problem solving, teaching you how to think like a programmer. It's a perfect place to start if you have no experience or background. The course is pretty flexible; you could do it at your own pace. They even give you a community to help you out.
Once you have your mindset established as a problem solver, now we can actually start to learn how to code. Here, we pick a coding language. For beginners, Python is highly recommended. It's easy to learn and widely used in pretty much everything from web development, data science, and machine learning. Other solid options are Java or JavaScript. They're great for backend and front-end software engineering, respectively.
Once you've chosen your language, dive into free resources like Codex.io, which makes you learn Python through a fun, video game-like environment. You solve challenges like writing for loops, conditionals, and creating functions to beat in-game enemies. You even get to dabble a little bit with object-oriented programming, which is essential for technical interviews. Or, if you want a simple, traditional way to learn, freeCodeCamp is a great resource, and they offer free Python lessons.
While learning the basics of coding, start building simple projects to put your knowledge into practice. That's where this whole "build to code" terminology comes from. For example:
- To-Do List App: This helps you understand user input, lists, and data persistence by allowing users to add, delete, and mark tasks as complete.
- Calculator: Here, you can practice implementing functions, conditionals, and basic arithmetic operations to perform calculations.
- Web Scraper: This introduces you to working with libraries like Beautiful Soup or Requests to extract and parse data from websites.
These small projects will help you understand how to actually apply concepts you learn, and you will not be stuck in tutorial hell henceforth.
Level 2: Develop Impactful Projects
Once you're comfortable with the basics of coding, it is time to go from level one to level two, and that is where we work on actual projects. The small projects in level one were a great start, but they won't actually count going forward. Projects are your work experience before you get formal work. When you're a full-time software engineer or even an intern, your day-to-day work is just doing various projects. Hence, before you get employed, you need to do quality projects on your own to showcase that you have the skills required for the job itself.
Here are several project ideas at various levels of difficulty:
Beginner: Personal Expense Tracker This is a practical tool that helps you manage your income and expenses by analyzing your spending habits. You can use libraries like Pandas for data manipulation and Matplotlib for creating visualizations like graphs and charts. To make it even more engaging, add a user interface by using Flask. If you do a really good job on this, you can even deploy it or sell it to other people to use as a side hustle.
Intermediate: Password Manager For a bit of a challenge, try building a password manager. This project introduces you to basic cybersecurity concepts and gives you a chance to work with Python's cryptography library by encrypting and securely storing passwords. You can create functional systems that retrieve them on demand. For a more polished experience, you can consider adding a GUI (graphical user interface) with Pygame. Because this is a pretty impactful project which affects the security of systems, depending on how you frame it verbally in interviews or even on your resume, this could become a pretty big deal.
Advanced: NLP Chatbot For a step above, consider creating a chatbot using NLP (Natural Language Processing). Start simple by training your chatbot to respond with predefined answers using Python's NLTK library. Once you've mastered the basics, you can integrate more sophisticated features like handling real-time conversations using APIs like Google Speech to enable voice interactions. Everyone nowadays has some sort of AI/machine learning project, so this project will give you the right amount of hands-on experience in that field while incorporating it into a software engineering workflow.
Overall, the specific technologies don't matter as much as the complexity and the impactfulness of the project itself. For example, if one person creates a machine learning weather application and someone else creates a simple web app that helps local restaurants reallocate and reduce food wastage by 50%, the second person is far more impressive because their project was way more impactful. You need to be able to explain the "why" behind your project. For more inspiration, check out the practical-tutorials repository on GitHub; it has many different project ideas for different programming languages, plus some tutorials.
Level 3: Build a Standout Resume
Now, we're going to kick it a further notch up. You have your background set; now let's transition into setting yourself up for a career in software engineering. Level three is your resume. We will now go over how to build a resume that can stand out amongst hundreds of thousands of applicants.
Let's break down the key sections of an effective resume.
Header: Your name should be bold and centered for easy recognition. Include two contact methods: your email for interviews and your phone number for technical screenings. Add your LinkedIn alias for your profile and your GitHub to showcase your projects and open-source contributions. If you are a US citizen with a non-traditional American name, it can be helpful to mention your citizenship status. Companies generally try to avoid sponsorships when they can, so highlighting your citizenship status might give you a little bit of an edge.
Education: Bold your school name and city, and italicize your degree and graduation date. If you are a student, make sure to explicitly use the words "Expected Graduation Date" on your resume because it subtly gives the psychological impression that you are a little older as a student. This is important because companies generally try to avoid hiring freshmen and sophomores. It can also be beneficial to list relevant coursework and even adjust course titles to better align with the technical skills that are optimized for Applicant Tracking Systems (ATS). For example, a course named "Intro to Computing" could be listed as "Computing and Python" if that more accurately reflects the skills you gained.
Experience: Be sure to use the XYZ format, which is recommended by Google for its engineers. It states that for each bullet point, you should say something along the lines of "accomplished X through Y resulting in Z impact." For example: "Developed a Python-based UI to track algorithmic performance, resulting in a 15% improvement in prediction accuracy." Numbers are essential because they quantify the impact and draw eyeballs to your resume. This could be a percent accuracy, leadership of a 200-member club, or a game with 8,000 app store downloads. No one actually cares about your projects unless you make them care, and by quantifying it, you do make them care.
Projects: For a project like a stock predictor, you would list models like Neural Networks, Naive Bayes, and Linear Regression, along with performance metrics, because numbers are important. Two big mistakes people make are either just listing project titles without any elaboration or listing technologies without explaining how they were used. The "through Y" part of the XYZ format is super important because employers don't just care that you know Java; they want to know how deeply you know it. Did you just use Java to develop a basic calculator, or did you use the Spring Boot framework to deploy a full-stack web application?
Activities and Leadership: You can put in university clubs you were part of, like a web development club where you learned HTML, CSS, and React, or a data science club where you gained skills in Python libraries like NumPy and TensorFlow. Even if you weren't deeply involved, you should emphasize the skills gained to stand out more in the ATS.
Skills: This is the only part of your resume where it's okay to not list items in full, detailed sentences. Avoid unnecessary qualifiers like "Python (Beginner)" or "Java (Intermediate)." It's a common belief that if you put a language on your resume, you should be at least intermediate in it. You don't need to be a full-on expert, but you should be good enough.
Overall, just make sure your resume is properly formatted.
Level 4: Navigate Applications and Secure Referrals
Coming in at level four, you have your resume and your experiences. Now, we need to actually get you a job, and for that, we have applications and referrals. The process of applying to jobs is straightforward: you go to career fairs, networking events, LinkedIn, GitHub, Reddit, Levels.fyi—pretty much apply anywhere and everywhere. The hard part is getting a call back because you're applying in an ocean of hundreds of thousands of candidates.
Insights from industry recruiters suggest that it's hard to get a call back because of AI that auto-applies to jobs for people. There are AI tools that scrape job boards, and as soon as a position opens up, they apply on behalf of users. A job posted just two minutes ago might already have over 200 applicants. This is due to mass applications.
So, how do you beat it? You need to get a referral. Referrals are no longer nice-to-haves; they are almost at the point where they are a must-have. When it comes to referrals, there are also three levels, and not all are created equal.
Level 1: The Basic Referral This is what everyone knows about. You reach out to someone who works at a company you're interested in, like Meta or Google. You ask them, "Hey, can you refer me?" You hand in your resume, and they put you in the system. You might get an interview, but nowadays, this is a little too common to be super effective.
Level 2: The High-Impact Referral This is a more strategic approach. You need to establish connections with hiring managers or at least people who are connected with them. Have them review your resume and vet you. The hiring manager is the one who ultimately makes the decision. If they like you based on your resume, you will at a minimum get a job interview.
Level 3: Inbound-Based Networking This is the most powerful method. If done right, you'll pretty much never have to physically apply to a job ever again. Consider the case of an engineer who, for his last two jobs, never had to interview. Why? Because he regularly posts about his coding projects on Twitter. The founders of the two startups he joined actually reached out to him via Twitter after seeing his amazing projects. Why would anyone have to evaluate you for your technical aptitude if you can prove it through your projects and online presence? Post about impactful projects you've worked on via LinkedIn and Twitter. Even in a competitive job market, an online presence can lead to hiring managers, founders, recruiters, and hiring agencies regularly reaching out. Developing your online presence in the tech sphere properly can transform the landscape of your career going forward.
Level 5: Ace the Technical Interview
Alright, so you have your background, your experiences, you've applied to jobs, you've gotten referrals, and now you have interviews coming up. You need to pass your interviews to actually land that offer. In this final level of the pyramid, we are going to be doing technical interview prep.
First, you actually have to learn your data structures and algorithms. For that, a great resource is cs.usfca.edu/~galles/visualization/Algorithms.html. It was developed by the University of San Francisco and features many different data structures and algorithms, showing you how they work visually.
For example, if we look at an Array List and want to add an item like the number 2, it will show the visualization of it being added, plus the code executing. You can even lower the animation speed to understand it better. It shows the exact pseudocode of how to go through the process so you understand it fundamentally. It's especially useful for graphs, specifically Depth-First Search (DFS). You can put in your start vertex, and it'll show you the code it's going through, but it'll also show you the different variables and what they hold as it's executing. It shows the list, the visited set, the current vertex, and the recursive stack, so you know where the function calls are going. This is super helpful for recursion. We also know DFS can be implemented with a stack, and the tool will show how that is done and how the elements within the visited set and current vertex change.
This is an excellent resource for beginners to learn data structures and algorithms. Once you learn a little bit, I would actually say go on to visualgo.net. It'll show you even more data structures and algorithms with more detailed code, helping you elevate your understanding to a more intermediate/advanced level. Let's take a look at a Binary Heap and construct it. The tool shows you the specific, proper code (not just pseudocode) and has an English explanation of what's happening. It tells you exactly what's being done, how it's swapping items as it's constructing the heap (since we have either a max heap or a min heap), and how it maintains the efficiency of O(n log n).
In combination, these resources should be an excellent starting point. Once you understand your data structures and algorithms, you actually have to practice for technical interviews, and for that, we need to practice LeetCode. Don't blindly go on LeetCode.com; you need to identify the problems you need to study. For example, if you have a technical coding interview for Amazon, you should search for "LeetCode Amazon questions." You'll get many resources of previously asked Amazon questions. There are websites dedicated to listing top questions from companies. You might encounter problems like "Find the K Smallest Pair Distance." You can also use Reddit's LeetCode community to identify these specific problems.
Okay, but let's just say you're on a problem like "Longest Substring Without Repeating Characters," and you're scratching your head. You know Python, but you just don't know how to piece together this problem. Don't worry; there's an excellent resource to help you out. Take the LeetCode question, copy it, and paste it into Google with "GeeksforGeeks" at the end. The first link will likely be a GeeksforGeeks article that will walk you through the solution. It'll first give you a naive approach, then a few optimized approaches. The reason this is great is that it gives you many different programming language options, so you can understand it pretty easily. It provides comments, and as you scroll down, you get to see the optimized approach and understand why it's optimized, with visual diagrams to help. Plus, it explains the time and space complexity, so you understand it even better.
It's not recommended that you just copy and paste this into the LeetCode editor because then you learn nothing. But it is recommended that you take a good look at it, read all the code, the English explanations, and the diagrams to really understand it. Then, close the window and go back to LeetCode to try to implement it for yourself. This way, you actually understand, practice, and get better, and hopefully, you can pass your technical interviews going forward.
