Staff Backend Engineer - Adaptive Telemetry, Databases

at Grafana Labs

📍 Canada

CAD 186,400-223,600 per year

SENIOR

✅ Remote

Used Tools & Technologies

Not specified

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Security @ 4 Go @ 4 Grafana @ 4 Kafka @ 3 Kubernetes @ 4 Prometheus @ 3 IaC @ 4 Python @ 4 Distributed Systems @ 4 Leadership @ 4 Communication @ 7 Rust @ 4 Microservices @ 4 Debugging @ 4 Technical Leadership @ 4 Observability @ 4 AI @ 4

Details

Grafana Labs is the company behind the open observability cloud and Grafana Cloud, a fully managed observability platform that integrates metrics, logs, traces, and profiles. The Databases department owns and operates the telemetry databases (Mimir for metrics, Loki for logs, Tempo for traces, and Pyroscope for profiles) and offers them as Cloud services supporting Grafana Cloud.

This role sits on the Adaptive Telemetry group within Databases and focuses on ensuring telemetry stored in our databases is optimized and worthy of attention via Adaptive Metrics, Adaptive Logs, Adaptive Traces, and Adaptive Profiles. This is a remote position; Grafana Labs is seeking candidates in Canadian time zones.

Responsibilities

Drive technical strategy and roadmap: define architectural vision, prioritize work that unlocks major product or platform improvements, and influence product and engineering decisions.
Lead end-to-end delivery of large, cross-functional projects: own planning, design, execution, rollout and long-term operation of large initiatives.
Own architecture, reliability, performance and cost for critical systems: make pragmatic choices balancing scalability, availability, latency and cost while keeping systems maintainable and evolvable.
Define SLOs/SLIs and lead incident response: establish measurable reliability targets, run high-severity incident response, lead blameless post-mortems, and drive systemic fixes and automation to prevent recurrence.
Improve observability, automation and operational readiness: champion telemetry, alerting, runbooks, capacity planning and automation to reduce toil, speed debugging and lower MTTR.
Align stakeholders and remove blockers: coordinate across Product, Design and other teams to align priorities, negotiate tradeoffs, and unblock delivery for large initiatives.
Mentor and grow engineering talent: coach senior and mid-level engineers, lead design reviews, raise engineering standards, and help teammates make sound technical tradeoffs.
Represent engineering internally and externally: communicate technical strategy clearly to non-engineering stakeholders and represent the team in cross-team planning.
Use modern AI coding assistants as part of the workflow if desired (company-funded budget and allowed within security guidelines).

Requirements

Proven delivery of large distributed systems with evidence of technical leadership and impact.
Strong systems-design instincts and deep understanding of tradeoffs around latency, consistency, availability, scaling and cost.
Hands-on cloud and platform experience with cloud-native architectures (microservices, containers/Kubernetes, IaC) and operational practices.
Reliability and performance ownership experience: defining SLOs/SLIs, capacity planning, tuning performance, and driving reliability work end-to-end.
Excellent coding and design skills: writes clear, maintainable, well-tested code. The team uses Go (other languages like Python, C, C++, Rust translate well).
Comfort with AI-assisted development and practical experience folding AI-powered developer tools into a team’s workflow is a plus.
Familiarity with streaming/messaging systems (e.g., Kafka) and observability tooling (Prometheus/Grafana or equivalents).
Strong communication skills and ability to influence without authority in a remote-first environment.

Technologies & Tools Mentioned

Go (primary language used)
Python, C, C++, Rust (translatable experience)
Kubernetes, containers, microservices
Infrastructure as Code (IaC)
Kafka (streaming/messaging)
Prometheus, Grafana, Mimir, Loki, Tempo, Pyroscope
SLOs/SLIs, observability and telemetry tooling
AI-assisted development tools (company-supported)

Compensation & Rewards

Canada base compensation range: CAD 186,368 - CAD 223,642 (actual compensation may vary based on level, experience, and skillset). Benefits include equity, bonus (if applicable), and other benefits listed by Grafana Labs. Compensation ranges are country-specific; applicants from other locations will have market-specific ranges discussed by the recruiter.

Why You’ll Thrive at Grafana Labs

100% remote, global culture with a scaling organization and transparent communication.
Innovation-driven environment, open source roots, empowered teams, and career growth pathways.
In-person onboarding and a global annual leave policy (30 days per annum, with 3 reserved Grafana Shutdown Days).

Equal Opportunity

Grafana Labs is an equal opportunities employer and welcomes applications from everyone regardless of protected characteristics. The company may utilize AI tools in recruitment to assist in matching CVs to job postings, with manual review by the recruitment team.