Tell me about a technical challenge you faced and how you overcame it.

In my first few months, I was assigned a small API change for a reporting feature, and I ran into a bug where certain customer names caused the endpoint to fail. It was tricky because normal test data worked, so at first it looked like my code was fine. I compared a failing request with a passing one, built a smaller reproduction, and found that one formatting step was dropping characters we later depended on. I fixed that logic, added a regression test with the exact failing case, and verified the endpoint still behaved correctly for the common path. I also asked a teammate to sanity check my reasoning before merging, which helped me confirm I had the root cause and not just a workaround. Since then, when something only fails on edge-case data, I try to create a minimal example before changing the code.

During a summer internship, I was helping add a small dashboard for tracking delivery status, and the tricky part was that the numbers didn’t match what support was seeing. I spent a lot of time checking my code before realizing the problem was in the data source: some orders were marked as complete in one system but still active in another. I worked with a more experienced engineer to trace the flow from the database to the page, then I added a small check that flagged those mismatches instead of silently counting them wrong. I also wrote a simple note for the team explaining the edge case, because support had been chasing the same issue without knowing why it happened. The project taught me that even small features can depend on data quality, and now I try to understand where the information comes from before I start coding.