Not just what I have done — but how and why I do it. Real answers to real interview questions.
How do you handle situations where different teams see the same problem differently?
I bring them into the process early. When everyone understands the why behind a decision — not just the what — alignment happens naturally. I have found that the best solutions rarely come from one perspective alone.
My approach is to map each team's view of the problem first, find where they overlap, and use that common ground as the starting point. The disagreements reveal assumptions nobody had made explicit. My job is to create the conditions where the right answer can emerge from the people closest to the problem.
Walk me through how you approach a problem you have never seen before.
I start by resisting the urge to jump to a solution. First I ask: what is actually broken? Not what people say is broken, but what the data and the workflow tell me. I map the current state, find where the pain originates, and separate symptoms from causes.
Then I look for analogues — have I solved something structurally similar before? If not, I research, prototype small, validate early, and build from there. I document as I go so whatever I build is explainable and repeatable.
Tell me about a time you identified a problem nobody else had noticed.
At EDGE Education, production cost and timing data was largely invisible. Teams were making resourcing and pricing decisions based on estimates and gut feel — not because they were careless, but because no system existed to capture the right signals.
I mapped the gap, designed the data capture workflow in Jira, built the reporting layer, and gave Finance and the PMO their first reliable cost-per-title view. That work ultimately led to the creation of my current role.
How do you get buy-in from people who are resistant to change?
I try to understand their resistance before I try to overcome it. Most people are not resistant to change — they are resistant to change that does not account for their reality. So I ask questions, listen properly, and factor their concerns into the design.
When people feel heard and see their input reflected in the solution, the resistance usually dissolves. And when it does not, I make the cost of the status quo visible — not to pressure, but to inform.
Describe your approach to leading a team through a high-pressure delivery.
Calm is contagious — so is panic. My first job under pressure is to stay steady so the team can too. I triage ruthlessly: what must ship, what can slip, what is a distraction. I make priorities explicit so nobody is guessing.
I check in frequently to surface blockers early and protect the team from noise. After delivery, I always run a retrospective — pressure reveals process gaps worth capturing.
How do you decide what to automate and what to leave manual?
My rule of thumb: if I do it twice, I think about scripting it. If I do it ten times, I script it. But before automating anything, I make sure I understand the process completely — automating a broken process just makes it break faster.
I also weigh maintenance cost against time saved. The goal is not automation for its own sake; it is freeing up human attention for work that actually requires judgment.
How do you ensure data accuracy in the systems you build?
I design for auditability from the start — logging inputs and outputs, validating transformations, and making data lineage visible. When a number looks wrong, you can trace exactly where it came from.
I build in sanity checks: expected ranges, row count validations, reconciliation against known totals. And I version queries and schemas so changes are tracked over time.
How do you use AI in your day-to-day work?
I treat AI as a research partner and code co-pilot — excellent for scaffolding, edge-case hunting, and first drafts. I use it to pressure-test ideas, generate SQL snippets, draft technical notes, and check logic quickly.
What I do not do: share sensitive data, skip validation, or ship AI-generated output I cannot fully explain. AI accelerates my work; it does not replace my judgment. The accountability stays with me.
Are you worried AI will replace your role?
Not really. The work I do is not just writing code or building reports — it is understanding what the business actually needs, translating that into a system, and making sure it keeps working. That requires context, judgment, and trust that AI cannot replicate on its own.
What AI changes is the baseline. Tasks that used to take hours take minutes. That means the value I provide needs to be at a higher level — more strategic, more focused on outcomes. I find that genuinely exciting.