Shaping the Future with Big Data: Shubham Bhatia’s MPCS Experience at SFU

When Shubham Bhatia joined SFU’s Master of Professional Computer Science (MPCS) program with a focus on Big Data, he already carried four years of experience from one of the world’s leading automotive engineering firms. But he was looking for something more,  a launchpad into the growing world of AI, scalable systems, and advanced software development.

Today, he works as a Software Engineer at Amazon Web Services (AWS), contributing to core messaging and streaming services used worldwide. He credits the MPCS program for sharpening his technical foundation, expanding his applied experience, and preparing him for large-scale engineering environments.

Shubham shared his experience and insights from pursuing the MSc in Big Data, one of the specialized pathways in our Master of Professional Computer Science (MPCS) programs, offering a glimpse into his unique journey.

Can you share your background before joining the Master's in Professional Computing Science program?

I completed my undergraduate degree in Information Technology from Vellore Institute of Technology, Vellore, India, in 2018, after which I worked for four years with Mercedes-Benz R&D India as a Software Engineer. I was part of the Navigation team, where I contributed to state-of-the-art algorithms and features for next-generation Mercedes-Benz vehicles. In 2022, I decided to take the next step in my career and moved to Canada to pursue the Master of Professional Computer Scienc e(MPCS) program, focusing on Big Data at SFU.

What motivated you to pursue this program?

By 2021, I found myself increasingly drawn to the growing impact of data science and machine learning in shaping the future of software systems. Although AI wasn’t as mainstream then, I wanted to strengthen my understanding of the fundamentals driving intelligent systems. The MSc Big Data program at SFU stood out for its applied focus, balanced mix of academic and real-world learning, and the opportunity to gain Canadian experience through its co-op component. It felt like the perfect bridge between my industry background and my long-term goals.

How did your career progress after graduation, and how did the MSc in Big Data prepare you for it?

After completing the program, I joined Amazon as a Software Engineer, where I now work on messaging and streaming services within AWS.

This professional master's program helped me build the ability to push through ambiguous problems and deliver high-quality, well-structured solutions — a skill that’s essential especially in large-scale engineering environments like AWS. The program’s mix of technical rigor, applied projects, and co-op experience gave me the confidence and the toolkit to take ownership of complex problems, collaborate effectively, and drive results in fast-moving, high-impact teams.

What skills or experiences from the program have been most valuable in your role at Amazon?

The machine learning, big data lab, and distributed systems courses were instrumental in refining how I think about the fundamentals of AI, data storage, optimization, and scaling software in general — all of which are crucial at Amazon. Just as importantly, the program’s emphasis on collaboration, applied projects, and clear technical communication helped me grow beyond coding — to think systemically and articulate ideas effectively.

Did you collaborate with industry or work on applied projects during your studies? If so, how did those experiences shape your skills? 

Yes — one of the highlights of the MPCS program was its strong emphasis on applied learning and industry collaboration. During my co-op term at Huawei Technologies, I worked on the Huawei Cloud team, where I helped develop core components for one of their cloud storage solutions.

Apart from the co-op, I also led two major applied projects at SFU. One being an LLM-based AI chatbot that allowed users to customize the chat bot to handle queries based on different models integrated in the backend. This project helped our team achieve a top 4 finish in a data science competition. In another project, we built a trend and sentiment analysis dashboard that predicted e-commerce product performance based on customer reviews. Both projects deepened my understanding of practical AI applications and reinforced how data-driven design and system thinking can come together to create impactful technology.

Together, these experiences shaped how I approach problem-solving today — whether it’s tackling complex problems or taking system reliability into account during the design phase, it taught me some important lessons in building software.

What advice would you give to prospective students considering this program?

The MPCS program can get intense, but it’s also one of those rare times in life where you’re surrounded by brilliant people, a friendly environment, and endless opportunities to experiment. Make the most of that.

If you’re not planning to go back to school after this, treat your time here as your sandbox — try new things, take on projects that excite you, and enjoy the ride. Also, talk to your professors. They’re incredibly approachable if you come prepared with thoughtful questions, and many of them have deep industry or research experience that can really shape your perspective.

And finally, start preparing early for your co-op hunt. Begin brushing up on your coding and problem-solving skills (a LeetCode a day, keeps unemployment away!) well before interview season kicks in — it’ll make things far less stressful later.

The Master of Professional Computer Science (MPCS) is a suite of three programs - MSc in Big Data, Master of Cybersecurity and Master of Visual Computing. Applications are currently upon until January 19, 2026.