Grafana Labs builds the LGTM stack — Loki (logs), Grafana (visualization), Tempo (traces), Mimir (metrics). The company is fully remote, deeply open-source, and the interview process reflects that: practical, async-friendly, and skeptical of pure LeetCode theatrics.
Process
Recruiter screen → 60-minute technical phone (often pair-coding on a small task) → onsite virtual loop: 1 coding (pair, often Go), 1 system design (always observability-flavored), 1 craft deep-dive, 1 behavioral, 1 hiring manager. Cycle: 3–5 weeks (slow because everyone is distributed).
What they actually ask
- Design a time-series database with horizontal scaling and 99.9% query SLA
- Design a distributed log aggregation system handling 100TB/day ingestion
- Design a metrics query engine with PromQL-style language and pushdown optimization
- Coding: practical problems in Go — parsers, queues, simple state machines
- Open source contribution review: be ready to walk through any past OSS work
Levels and comp (2026)
- SE II: $160K–$200K total
- Senior SE: $230K–$300K
- Staff: $330K–$430K
- Principal: $450K–$580K
Prep priorities
- Be fluent in Go — it is the lingua franca of the LGTM stack
- Understand columnar storage, time-series compression, and Prometheus internals
- Demonstrate genuine OSS engagement — issues, PRs, blog posts all count
Frequently Asked Questions
Is Grafana Labs really fully remote?
Yes. Hubs in NYC, London, Stockholm, Sydney exist but are optional. 600+ employees in 50+ countries.
Do I need observability experience?
Not strictly. They hire generalists who are excited to learn. Curiosity about Prometheus or having read their docs goes a long way.
How does Grafana Labs compare to Datadog?
Datadog pays more cash but is closed-source SaaS. Grafana is OSS-first, more remote-friendly, and has strong “build in public” culture.