Building Trust Through Data
Yara Burvin, Analytics Engineer in London, shares how she built a game-changing data hub that transformed FinCrime operations at Wise. Read more below 🚀
"At Wise, I have the trust from day one to make decisions and take ownership of real work. This trust helped me gain confidence and grow as an engineer."
Yara Burvin (She/Her)
Analytics Engineer
Tell us about your journey to joining Wise
Before joining Wise, I worked at another fintech where I began my career in Analytics and Data Engineering, quite a shift from my background in chemistry! That scientific foundation actually gave me strong analytical skills, but I was eager to find a role that would push me to my full potential and challenge me to try new things.
What drew me to Wise was discovering that the analytics engineering team played a central role here, allowing for collaboration across both data engineering and analytics. This wasn't just about crunching numbers in isolation, it was about working directly with stakeholders, joining new projects, and making a real impact on how we serve our customers.
The technical nature of the role, combined with Wise's mission of making money work for everyone, made this the ideal place for me to grow. I love that we're not just building dashboards, we're creating tools that help protect our customers and make their financial lives easier.
What are some key projects you're working on?
I'm currently focused on developing a comprehensive data hub that consolidates all our financial crime and Know Your Customer (KYC) cases into a single, unified source of truth. This project has now reached a significant milestone — the data hub is live and actively used by various teams across the company.
Before this, there was no centralized location to find answers to important questions such as:
How many suspensive cases did we have last quarter?
How many cases where customer activity is temporarily halted until an issue is resolved?
You'd have to search through multiple sources and hope you found everything. There was no straightforward way to assess how long these cases typically take to resolve or how different teams are managing them.
Now, all that information is readily accessible in one place. Teams can analyze and address financial crime and KYC cases more effectively, leading to better decision-making and streamlined operations. What I love most is how this directly impacts our customers — faster case resolution means people get access to their money quicker.
Being involved in this project has been incredibly rewarding. I love how open-minded my team and stakeholders are to trying new things and collaborating on innovative ideas. This environment allows us to elevate our solutions based on what the business actually needs. There's something really satisfying about discussing a problem, working collaboratively to solve it, and seeing the results in real time.
Are there tools you couldn’t do your job without?
DBT (Data Build Tool) is absolutely essential for us. It's a powerful tool that allows us to manage and build our data pipelines efficiently, transforming raw data into structured formats that can be easily analyzed. Without DBT, we'd be drowning in messy data that nobody could make sense of.
But it's not just about building pipelines, we also keep a close eye on cost and performance. Part of my role involves developing and utilizing a cost monitoring model to oversee spending and track the performance of all analytics models. I also help teams write better, more efficient code, optimizing pipelines, tracking tool usage, and improving dashboard load times.
This might sound technical, but it has real business impact. When dashboards load faster and pipelines run more efficiently, teams across Wise can make decisions quicker. That efficiency ultimately flows through to better customer experiences.
What advice would you offer to someone pursuing a career in analytics engineering?
To build a strong foundation in both data engineering and analytics, you need to understand how data flows and how to extract insights from it. But don't think you need to be a coding wizard from day one. I came from chemistry, and that scientific thinking actually helps a lot in this field.
Stay curious about industry trends and make an effort to network with others in the field. The analytics engineering community is really collaborative, and there's always someone willing to share knowledge or help solve a tricky problem.
Most importantly, don't worry if you don't come from a highly technical background. Diverse experiences are actually a strength in this field, they help you ask different questions and approach problems from unique angles. Embrace the opportunity to learn on the job, because in analytics engineering, you're always learning something new.
The field is evolving rapidly, and Wise is always looking for people who can bridge the gap between technical capabilities and business needs. If you enjoy solving puzzles and seeing the direct impact of your work, this could be the perfect career path.
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