10 Minutes With: Ajlaan Bridle

In this edition of 10 Minutes with, we get to know Aj, a Data Engineer turned Team Lead at RedCloud who has been making significant strides in data solutions for one of our largest accounts at Google. From architecting critical compliance and risk management projects to mentoring a growing team spread across the U.S. and offshore, Aj shares insights into his professional journey, what drives his continuous growth, and even a surprising hobby that keeps him balanced.

Read on to learn more about Aj’s professional philosophy, his favorite quote that keeps him grounded in technical work, and a few fun facts that reveal the person behind the data.

Describe your role and what you do in a nutshell. 

I joined RedCloud a year ago as a Data Engineer on a four-person team supporting a new account at Google. My primary role was to architect and deliver data solutions for stakeholders in Google’s Compliance, Safety, and Risk Management organization. Since then, the team has expanded to 12 Data Analysts and Engineers based in both the U.S. and offshore. I recently transitioned into the role of Team Lead. My current responsibilities include maintaining a high-level view of our growing project portfolio, managing task assignments, removing blockers, and providing technical mentorship to help our highly skilled team reach its full potential.

What are you most proud of in your career so far? 

I’ve had the pleasure of working across multiple industries, and one experience I look back on with great pride is leading noise certification testing for a jet engine manufacturer. I had the opportunity to build strong relationships with a high-profile international customer, collaborate across various departments within a large organization to plan and execute full-scale hardware testing, and even travel overseas. One project that stands out involved working closely with technical specialists to reach a critical milestone through in-depth technical analysis instead of additional engine testing—ultimately preventing unnecessary costs (and jet fuel burn!) 

Share your go-to methods for professional development or personal growth. 

I guess my preferred way of developing professionally is when it’s ‘ambient’—as in, my day-to-day work provides new challenges that I can sustainably stretch and grow from. An entire career is a long time, and for me, stacking incremental growth has served me well. This mindset has potentially been influenced by my powerlifting hobby, which heavily emphasizes embracing the training process to achieve longer-term gains.

If you could suggest a book for the entire team to read, what would it be and why? 

I’ve recently found myself binging some of the Murderbot Diaries books, written from the perspective of an android with a dry sense of humor. My immediate colleagues would probably tell you that I like to foster a lighthearted office atmosphere, so perhaps my suggestion would be less toward something specific and more toward something that’ll make you actually laugh out loud!

What's a piece of obsolete technology you still have a soft spot for? 

It’s not obsolete by any means, but I find reading a physical book to be a more comfortable experience than reading through a screen.

What's one thing people don't know about you that they would be surprised to discover? 

I love to make sourdough pizza from scratch! It’s a pandemic hobby that ended up sticking. I found a recipe for the crust and sauce that worked great for me, and I’ve largely stuck with them, making minor tweaks here and there to improve them even further. Things like dusting the dough balls with semolina flour before stretching them out, baking the pizza twice in a home oven (first with just the sauce, then with toppings) for an extra-crispy crust, or shredding a block of low-moisture mozzarella instead of using pre-shredded cheese.

Share one of your favorite quotes. 

A former mentor used to say, “All models are wrong – some are useful.” This has kept me grounded in a couple of ways when in the trenches of detailed technical work: I have a healthy skepticism of model or analysis output (especially predictive outputs), and I recognize that a tool or model doesn’t have to be perfect to add genuine value.