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The Bar Raiser's Debrief · Amazon Software Development Engineer

"Tell me about a time you went deep into data or technical detail to solve a problem"

Dive Deep Software Development Engineer 5–7 min
Why candidates fail: Candidates describe what data they looked at instead of showing the non-obvious insight they uncovered that no one else had found.
Two voices. One question. The insider reaction you don't usually see.
Also on YouTube 5–7 min 2026
"Tell me about a time you went deep into data or technical detail to solve a problem"
Competency tested
Dive Deep
Who asks it
Bar Raiser · HM · Peer
What they're really asking
Did you find what your team missed?
The answer that fails — and why
Candidate answer Does not raise the bar — Dive Deep

We had a service that was showing elevated latency in our dashboards. I pulled the CloudWatch metrics and dug into the logs to identify where the slowdown was happening. After reviewing the data, I traced the issue to a database query that was running a full table scan. I worked with the team, we added an index, and latency dropped back to normal. The whole investigation took about two days and the fix was deployed the following week.

Bar Raiser evaluation
Describes process steps, not a non-obvious insight discovered
No signal that depth exceeded team expectation or prior investigation
Outcome is routine; no mechanism or lasting change demonstrated
Prefer to hear it? Watch the video for the two-voice delivery with live reaction commentary.
Amazon debrief · SWE loop · Bar Raiser evaluation Below Bar
Leadership Principle: Dive Deep
Does not demonstrate Dive Deep.
Candidate described a standard debugging workflow, not a deep independent investigation.
No evidence the team had already looked at this and missed it.
Insight — full table scan — is the first thing any engineer would check.
No mechanism established; no signal this prevented future recurrence at scale.
interview101.com · Dive Deep · Amazon SWE · Bar Raiser debrief reference
Now here's what a strong answer actually sounds like
The answer that works — in full
Strong answer Raises the bar — Dive Deep

Our payment service showed a p99 latency spike every Tuesday at 11 AM. My team had already investigated twice and closed it as a traffic anomaly. I was not convinced. I pulled six weeks of raw request logs — not the aggregated CloudWatch metrics everyone had been using — and correlated them with our DynamoDB consumed-capacity data hour by hour. I found that a weekly batch job from a separate team was saturating our shared partition key. No one had made that cross-team connection. I brought the data to both teams, we repartitioned the key and isolated the batch workload, and p99 dropped from 800ms to 60ms permanently. I also documented the investigation pattern as a runbook so on-call engineers could detect cross-team contention automatically going forward.

Bar Raiser evaluation
Went deeper than the team had already gone — twice
Non-obvious insight: cross-team partition contention missed by everyone
Specific metric before and after: p99 800ms to 60ms
Mechanism created: runbook prevents recurrence, extends impact beyond the fix
Amazon debrief · SWE loop · Bar Raiser evaluation Raises Bar
Leadership Principle: Dive Deep
Strong signal. Raises the bar.
Explicitly went deeper than team's prior two investigations — strong Dive Deep signal.
Used raw data, not aggregated metrics — shows genuine analytical independence.
Cross-team insight was non-obvious and had been missed by multiple engineers.
Created a reusable runbook — turned a one-time fix into a durable mechanism.
interview101.com · Dive Deep · Amazon SWE · Bar Raiser debrief reference
Run your story through these three questions
1
Had your team already looked at this and concluded it was fine?
If not, you are describing expected work, not going deeper than anyone else.
2
Does your story name a specific insight no one else had connected?
Without a non-obvious finding, you are listing tools you used, not demonstrating depth.
3
Did your investigation produce a mechanism, not just a one-time fix?
Dive Deep at Amazon means your findings raise standards, not just resolve a ticket.
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Other questions from the same loop
Each video covers a different competency tested in the Amazon Software Development Engineer loop
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