Honeycomb is the technically respected observability-for-engineers platform — wide events, high-cardinality fields, BubbleUp anomaly detection. The engineering team is thoughtful, opinionated, and extremely public about what they do (Charity Majors’ blog, the Honeycomb engineering blog, and SREcon talks). The interview is async-friendly, writing-focused, and rewards engineers who already engage with their content.
Process
Recruiter screen → take-home async work sample (paid, ~3 hours) → 60-minute pair-programming → 60-minute system design → 60-minute past-project deep dive → behavioral. Cycle: 3–5 weeks.
What they actually ask
- Design a high-cardinality event store optimized for slice-and-dice queries
- Design distributed tracing ingestion at 1M spans/sec
- Design BubbleUp — automated anomaly detection across hundreds of fields
- Coding: Go (the bulk of the codebase), often involving streaming or columnar processing
- Behavioral: collaboration, writing skill, customer empathy for developer audiences
Levels and comp (2026)
- SE II: $170K–$210K total
- Senior SE: $240K–$310K
- Staff: $340K–$440K
- Principal: $470K–$610K
Prep priorities
- Read the Honeycomb blog and OpenTelemetry docs — Honeycomb employees lead OTel
- Be fluent in Go and at least one observability stack (Prometheus, Grafana, Tempo)
- Understand columnar storage, time-series compression, and trace data models
Frequently Asked Questions
Is Honeycomb fully remote?
Yes. Distributed across US and Canada with some EU presence. ~250 employees.
How does Honeycomb compare to Datadog?
Datadog is broader (infra + APM + logs). Honeycomb is deeper on developer-debugging via wide events. Smaller team, smaller comp, but more interesting engineering for many candidates.
What is the take-home like?
Realistic and bounded — a couple hours of work. They pay for it. Quality of writing and reasoning matters more than completeness.