Have you ever wondered why some data scientists decide to switch to engineering roles like data engineering, software engineering, or solutions architecture? I know I have.
As a data science enthusiast, I’ve often found myself curious about the motivations behind this career shift. What drives someone to leave the world of data modeling and machine learning behind and dive into the realm of code and system design?
To find out, I spoke with several professionals who have made the transition from data science to engineering. Here’s what they had to say.
## The Rationale
For many, the reason for switching is a desire for more hands-on work. As a data scientist, you often focus on analyzing and interpreting data, but you may not be involved in the actual implementation of your findings. In engineering roles, you have the opportunity to build and deploy solutions that have a direct impact on the business.
Others are drawn to the creativity and problem-solving aspects of engineering. “As a data scientist, I was limited to working within existing frameworks and tools,” said one professional who made the switch. “In engineering, I have the freedom to design and build my own solutions from scratch.”
## The Push Factors
So, what motivates someone to make the leap from data science to engineering? For some, it’s a desire for better job prospects or higher salaries. According to Glassdoor, the average salary for a data engineer in the United States is over $140,000 per year, compared to around $118,000 for a data scientist.
Others may be driven by a sense of boredom or stagnation in their current role. “I was doing the same thing every day, and I felt like I wasn’t learning or growing anymore,” said another professional who switched to engineering. “In my new role, I’m constantly faced with new challenges and opportunities to learn.”
## The Experience
So, how has the experience been for those who have made the switch? The consensus is overwhelmingly positive. “I feel like I’m making a real impact in my new role,” said one professional. “I’m not just analyzing data; I’m building solutions that drive business results.”
Of course, there are challenges to overcome, too. Many professionals reported feeling overwhelmed by the sheer amount of new information they had to learn, from programming languages to system design principles.
## Final Thoughts
If you’re a data scientist considering a switch to engineering, know that you’re not alone. Many professionals have made the leap and found it to be a rewarding and challenging career move.
It’s not for everyone, of course. But if you’re looking for a new challenge, a chance to be more hands-on, or simply a change of pace, engineering might be worth exploring.
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*Further reading: [Data Engineering vs. Data Science: What’s the Difference?](https://towardsdatascience.com/data-engineering-vs-data-science-whats-the-difference-3c2a5e8e6f5f)*