Sample Answer
On my last team, our order details API was one of the top endpoints and was consistently timing out under load. Median latency was around 850 ms and p95 was over 3 seconds for about 1.2M daily calls. I profiled the endpoint and found an N+1 query pattern plus some unnecessary joins. We consolidated it into two parameterized queries, added a Redis cache for the most frequently requested parts, and introduced a simple read‑through cache invalidation strategy tied to order updates. I also added basic query observability with slow query logs and per‑endpoint metrics in Prometheus. Within two sprints, median latency dropped to ~140 ms and p95 to under 500 ms. Database CPU went down about 35%, and we were able to reduce our DB instance size one tier, saving roughly 20% on that service’s infra cost. We also saw timeouts fall from ~4% to well below 0.2%.
Keywords
Walk me through a recent multi-channel digital marketing campaign you managed end-to-end. How did you set objectives, choose channels, allocate budget, and measure success?
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