If you dream of working at Google, one of the first questions you’ll ask is: What degree do I need? The truth is, there’s no single answer.
While a Computer Science (CS) degree is the most common path, Google has hired engineers with backgrounds in Mathematics, Electrical Engineering, and even non-technical fields.
But if you’re planning your education with Google in mind, let’s explore the best options.
Short answer? No. Google has eased its degree requirements over the years. What matters most is your skills, problem-solving ability, and experience.
However, having a relevant degree can make your path smoother, especially if you’re applying without industry experience.
Here’s what Google prioritizes:
Coding proficiency: Data structures, algorithms, and System Design are key.
Practical experience: Open-source contributions, internships, or personal projects.
Problem-solving ability: Can you think critically and optimize solutions?
Learning adaptability: Technology evolves, and so should you.
That said, let’s break down the best degree for a Google job based on different career goals and interests.
Grokking the Coding Interview Patterns
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A CS degree remains the most direct and reliable path to Google. It provides a strong foundation in programming, algorithms, and System Design—all of which are essential for Google’s technical interviews.
Key topics covered:
Data structures and algorithms – A must for technical interviews.
Operating systems and networks – Essential for backend and infrastructure roles.
Software engineering principles – Clean code, design patterns, and testing.
Artificial Intelligence and Machine Learning – Useful for AI-focused roles.
If you’re serious about software engineering, backend development, or AI, this is the way to go.
A Software Engineering degree is similar to CS but with a more hands-on, project-based approach. If you prefer real-world coding over theory, this might be a better fit. It’s ideal for roles in:
Full-stack development: Frontend, backend, and databases.
Mobile development: Android and iOS engineering.
Software architecture: Designing scalable applications.
This is a solid option for those targeting engineering roles where applied experience is critical.
Quick Start Full Stack Web Development
If you want to get into full stack web development, then you’re in the right place. This course is for anyone who wants to learn how to build a complete web application from front to back while avoiding the endless debates about product X versus product Y. Through this course you'll work with some of the most fundamental tools that full stack developers use everyday such as: React, Flask, SQL, creating APIs, testing, and more. Beyond that, you'll learn how to design an application from scratch, build the data model, and how to deploy it. By the end of this course, you'll have the skills necessary to create an application from scratch as well as a nice new project to add to your portfolio. Needless to say, this is your one-stop-shop to becoming a modern full stack developer!
Not all Google jobs are about writing app code. If you’re interested in hardware, networking, or embedded systems, an Electrical Engineering (EE) degree can be highly valuable. Google hires EE grads for roles in:
Embedded systems engineering: Building low-level firmware and drivers.
Network engineering: Optimizing Google’s global infrastructure.
Hardware design: Working on custom silicon chips like Google’s TPUs.
If you enjoy working at the intersection of hardware and software, EE could be your gateway to Google.
Google relies heavily on big data, Machine Learning, and AI-driven insights. A strong foundation in Mathematics or Statistics can open doors to fields like:
Machine Learning engineering: Training AI models for Google Search & Assistant.
Data science and analytics: Extracting insights from massive datasets.
Algorithm research: Optimizing search ranking and ad recommendations.
If you love probability, linear algebra, and optimization, this path is worth exploring.
Become a Machine Learning Engineer
Start your journey to becoming a machine learning engineer by mastering the fundamentals of coding with Python. Learn machine learning techniques, data manipulation, and visualization. As you progress, you'll explore object-oriented programming and the machine learning process, gaining hands-on experience with machine learning algorithms and tools like scikit-learn. Tackle practical projects, including predicting auto insurance payments and customer segmentation using K-means clustering. Finally, explore the deep learning models with convolutional neural networks and apply your skills to an AI-powered image colorization project.
Absolutely. Many engineers at Google don’t have a traditional CS background. They’ve built their skills through bootcamps, self-study, and real-world experience.
Here’s what works:
Learning coding through online courses & bootcamps (Coursera, Educative, etc.).
Building real-world projects and contributing to open-source.
Mastering data structures & algorithms (LeetCode, HackerRank).
Networking & getting referrals from current Google employees.
Google values skills over degrees. If you can demonstrate technical excellence, your background won’t matter as much.
For most software engineering roles, a bachelor’s degree or equivalent experience is enough. But in some specialized areas, advanced degrees can be beneficial:
Master’s in AI/ML: A boost for Machine Learning Engineers.
PhD in Computer Science: Ideal for research-focused positions.
MBA: Useful for Product Management and business-oriented roles.
For most engineers, experience and projects matter more than a Master’s or PhD. But if you’re diving deep into AI or research, it can be worth considering.
Not every role at Google is technical. If your strengths lie elsewhere, these degrees may align with non-engineering roles:
Design or HCI (Human-Computer Interaction): For UX/UI design roles.
Business or marketing: For roles in product marketing, growth, or sales.
Psychology or education: For roles in user research, learning science, or content strategy.
These paths still require strong analytical and communication skills, and some technical literacy is a plus.
Regardless of your degree, here’s what interviewers care about:
Problem-solving and analytical thinking.
Communication and collaboration skills.
Your ability to write clean, efficient code.
Understanding of scalable System Design.
Curiosity, humility, and willingness to learn.
Your degree helps get you in the door—but what you do with it matters even more.
If you’re applying from outside the U.S., your degree may be evaluated differently:
Make sure your transcripts are translated and comparable to U.S. standards.
Google often looks for equivalent coursework and projects.
Consider supplementing your degree with certifications or online credentials.
Strong projects and interview performance often outweigh the name of your school.
Transitioning into tech? Many successful Googlers began in unrelated fields:
Physics, biology, even music majors have landed engineering roles.
Focus on transferable skills like logic, problem-solving, and project ownership.
Build a strong GitHub portfolio to showcase your learning curve and code quality.
Self-taught developers are welcome—if you can code, you can compete.
If you’re still in school, combining majors can open more doors:
CS + Math is great for ML/AI.
CS + Business is ideal for Product Management.
CS + Design helps for roles in UX Engineering.
Interdisciplinary backgrounds are valued for roles that require both tech depth and domain knowledge.
Adding a minor can round out your skillset:
A math minor enhances your algorithms and ML credibility.
A psychology minor helps with human-centered design.
A communication or writing minor strengthens documentation and collaboration skills.
Choose a minor that complements your primary interest while adding soft skills.
If you’re considering a coding bootcamp, here’s what to keep in mind:
Bootcamps are fast and immersive but may lack the CS theory Google values.
Supplement your learning with System Design, OS, and algorithms.
Show depth through side projects and contributions to real-world systems.
Some Googlers started at bootcamps—just make sure you demonstrate CS fundamentals.
Not at all. Google hires career changers, older grads, and people from unconventional paths:
If you can solve hard problems and think clearly, your timeline doesn’t matter.
Many engineers enter Google after years in other industries.
The key is showing up prepared, skilled, and ready to learn.
It’s not about when you start—it’s about how well you execute.
The best degree for a Google job depends on your interests and career goals. A CS degree is the safest bet, but if you specialize in AI, networking, or even business, there’s still a path for you.
At the end of the day, Google cares about what you can build and how you solve problems. Whether you have a degree or not, the key is developing strong technical skills and proving your ability to innovate and think critically.
So—what’s your background? Did your degree help, or did you take an unconventional route?
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