Staff Backend Engineer - Grafana Databases, Managed Services
This is a remote opportunity and we would be interested in applicants from USA time zones only at this time.
Staff Backend Engineer - Grafana Databases, Managed Services
The Opportunity:
The Managed Services team is a newly formed squad within the Databases department. It owns and operates shared, production-critical infrastructure that powers Grafana Cloud’s next-generation database products (Mimir, Loki, and Tempo). Today, this includes operating 100+ WarpStream clusters across multiple cloud providers and regions, with continued growth anticipated for the future. WarpStream acts as the streaming backbone for ingestion and read/write decoupling across databases. It sits directly on the hot path for metrics, logs, and traces, handling high-throughput, multi-consumer workloads at massive scale.
In addition to streaming infrastructure, the team works closely with high-volume analytical and storage systems that power query-heavy and aggregation-heavy workloads, where latency, compression behavior, storage layout, and scaling characteristics matter deeply.
What You’ll Be Doing:
As a Staff Engineer on Managed Services, you will operate at both the system and team level. You will help shape how we run and evolve shared database infrastructure while remaining deeply hands-on in production. This involves:
Operating and evolving 100+ multi-cloud streaming clusters and related database infrastructure
Diagnosing and eliminating cross-layer failure modes (e.g., object storage latency, noisy neighbors, control-plane bottlenecks, query performance regressions, etc.)
Designing safe upgrade and rollout strategies at scale
Improving observability, automation, and operational ergonomics
Partnering closely with database and platform teams to ensure safe scaling, partitioning, consumer fan-out, and query performance
Working directly with distributed systems behavior, Kubernetes scheduling dynamics, storage engines, compression trade-offs, etc.
Serving as a primary escalation point and on-call for relevant incidents
Owning the relationship with all system vendors, including WarpStream Labs and others.
At the Staff level, your scope includes advanced systems ownership and informal technical leadership:
Help define and evolve the technical direction for operating WarpStream and adjacent shared database systems at scale
Lead complex initiatives such as migrations, rollout improvements, and reliability investments
Establish best practices around SLOs, scaling limits, failure isolation, and change safety
Investigate and drive resolution of multi-layer incidents spanning storage, compute, networking, and control-plane dependencies
Identify systemic risks across 100+ clusters and contribute architectural improvements that reduce recurring issues
Improve systems toil and operational ergonomics with automation
Partner with database and platform teams to align on strategy and long-term scalability
Mentor and support engineers as the team matures
As we are remote-first and our engineering organization is largely remote, we provide guidance and meet regularly using video calls, so an independent attitude and good communication skills are a must.
Of course, there is an on-call component to this role and one that we take seriously. As a company, we hire globally (remote-first) to ensure our on-call remains healthy and aligned to approximately 12 daylight hours per day. You will work closely with counterparts in other regions to provide balanced coverage and shared ownership.
This role blends deep distributed systems work with the opportunity to influence how the team approaches reliability, scaling, and operational excellence.
We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always paired with strong code review and quality standards. You’ll also have access to frontier models (e.g., GPT-Codex 5/3, Claude Opus 4.6, Gemini 3 Pro).
What Makes You a Great Fit:
Regular 1:1s with your manager and close collaboration with teammates across regions, helping shape how the team operates and matures
Defining and evolving SLO strategy for shared database infrastructure, identifying systemic reliability gaps and driving long-term error budget improvements
Setting standards for diagnosability across core streaming and database systems in production
Leading complex initiatives across high-throughput, multi-cloud infrastructure
Designing and promoting fault-tolerant architectural patterns that address distributed system realities such as storage latency, partition imbalance, noisy neighbors, and control-plane dependencies
Defining rollout, migration, and upgrade safety practices used across dozens of production clusters
Partnering with database and platform engineering leaders to influence architecture decisions, roadmap prioritization, and long-term scalability strategy
Leading design discussions and reviewing PRs with a focus on reducing operational risk and increasing system resilience
Raising the bar for practices across teams by mentoring engineers and sharing distributed systems knowledge
Playing a key role in high-impact incident response, guiding investigation, driving root cause analysis, and ensuring durable remediation through strong post-incident reviews
Requirements:
8+ years of engineering experience, including meaningful time in SRE, platform engineering, production engineering, infrastructure engineering, or distributed systems roles.
Experience with high-throughput streaming systems, analytical or storage backends, or large-scale database infrastructure. Examples of these include Kafka, Redpanda, WarpStream, Postgres, ClickHouse, Snowflake, or Cassandra.
Strong Kubernetes experience in AWS, GCP, or Azure, and familiarity with infrastructure-as-code tooling (Helm, Terraform, Jsonnet, etc.).
Experience leading or driving complex technical efforts, even without formal management responsibilities
Ability to influence technical direction and align teams around reliability improvements
Strong understanding of distributed systems failure modes in multi-cloud environments.
Proficiency in at least one systems-oriented language (Go preferred, but not required).
Working knowledge of Linux internals, networking, cloud storage, and performance/scaling behavior.
Experience participating in blameless incident response and writing high-quality post-incident reviews.
Clear communicator who can collaborate across teams and work autonomously.
Intellectually curious, transparent, action-oriented, and kind (this is important!)
Compensation & Rewards:
In the United States, the Base compensation range for this role is USD 174,986- USD 209,983. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here.
All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally.
About the job
Apply for this position
Staff Backend Engineer - Grafana Databases, Managed Services
This is a remote opportunity and we would be interested in applicants from USA time zones only at this time.
Staff Backend Engineer - Grafana Databases, Managed Services
The Opportunity:
The Managed Services team is a newly formed squad within the Databases department. It owns and operates shared, production-critical infrastructure that powers Grafana Cloud’s next-generation database products (Mimir, Loki, and Tempo). Today, this includes operating 100+ WarpStream clusters across multiple cloud providers and regions, with continued growth anticipated for the future. WarpStream acts as the streaming backbone for ingestion and read/write decoupling across databases. It sits directly on the hot path for metrics, logs, and traces, handling high-throughput, multi-consumer workloads at massive scale.
In addition to streaming infrastructure, the team works closely with high-volume analytical and storage systems that power query-heavy and aggregation-heavy workloads, where latency, compression behavior, storage layout, and scaling characteristics matter deeply.
What You’ll Be Doing:
As a Staff Engineer on Managed Services, you will operate at both the system and team level. You will help shape how we run and evolve shared database infrastructure while remaining deeply hands-on in production. This involves:
Operating and evolving 100+ multi-cloud streaming clusters and related database infrastructure
Diagnosing and eliminating cross-layer failure modes (e.g., object storage latency, noisy neighbors, control-plane bottlenecks, query performance regressions, etc.)
Designing safe upgrade and rollout strategies at scale
Improving observability, automation, and operational ergonomics
Partnering closely with database and platform teams to ensure safe scaling, partitioning, consumer fan-out, and query performance
Working directly with distributed systems behavior, Kubernetes scheduling dynamics, storage engines, compression trade-offs, etc.
Serving as a primary escalation point and on-call for relevant incidents
Owning the relationship with all system vendors, including WarpStream Labs and others.
At the Staff level, your scope includes advanced systems ownership and informal technical leadership:
Help define and evolve the technical direction for operating WarpStream and adjacent shared database systems at scale
Lead complex initiatives such as migrations, rollout improvements, and reliability investments
Establish best practices around SLOs, scaling limits, failure isolation, and change safety
Investigate and drive resolution of multi-layer incidents spanning storage, compute, networking, and control-plane dependencies
Identify systemic risks across 100+ clusters and contribute architectural improvements that reduce recurring issues
Improve systems toil and operational ergonomics with automation
Partner with database and platform teams to align on strategy and long-term scalability
Mentor and support engineers as the team matures
As we are remote-first and our engineering organization is largely remote, we provide guidance and meet regularly using video calls, so an independent attitude and good communication skills are a must.
Of course, there is an on-call component to this role and one that we take seriously. As a company, we hire globally (remote-first) to ensure our on-call remains healthy and aligned to approximately 12 daylight hours per day. You will work closely with counterparts in other regions to provide balanced coverage and shared ownership.
This role blends deep distributed systems work with the opportunity to influence how the team approaches reliability, scaling, and operational excellence.
We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always paired with strong code review and quality standards. You’ll also have access to frontier models (e.g., GPT-Codex 5/3, Claude Opus 4.6, Gemini 3 Pro).
What Makes You a Great Fit:
Regular 1:1s with your manager and close collaboration with teammates across regions, helping shape how the team operates and matures
Defining and evolving SLO strategy for shared database infrastructure, identifying systemic reliability gaps and driving long-term error budget improvements
Setting standards for diagnosability across core streaming and database systems in production
Leading complex initiatives across high-throughput, multi-cloud infrastructure
Designing and promoting fault-tolerant architectural patterns that address distributed system realities such as storage latency, partition imbalance, noisy neighbors, and control-plane dependencies
Defining rollout, migration, and upgrade safety practices used across dozens of production clusters
Partnering with database and platform engineering leaders to influence architecture decisions, roadmap prioritization, and long-term scalability strategy
Leading design discussions and reviewing PRs with a focus on reducing operational risk and increasing system resilience
Raising the bar for practices across teams by mentoring engineers and sharing distributed systems knowledge
Playing a key role in high-impact incident response, guiding investigation, driving root cause analysis, and ensuring durable remediation through strong post-incident reviews
Requirements:
8+ years of engineering experience, including meaningful time in SRE, platform engineering, production engineering, infrastructure engineering, or distributed systems roles.
Experience with high-throughput streaming systems, analytical or storage backends, or large-scale database infrastructure. Examples of these include Kafka, Redpanda, WarpStream, Postgres, ClickHouse, Snowflake, or Cassandra.
Strong Kubernetes experience in AWS, GCP, or Azure, and familiarity with infrastructure-as-code tooling (Helm, Terraform, Jsonnet, etc.).
Experience leading or driving complex technical efforts, even without formal management responsibilities
Ability to influence technical direction and align teams around reliability improvements
Strong understanding of distributed systems failure modes in multi-cloud environments.
Proficiency in at least one systems-oriented language (Go preferred, but not required).
Working knowledge of Linux internals, networking, cloud storage, and performance/scaling behavior.
Experience participating in blameless incident response and writing high-quality post-incident reviews.
Clear communicator who can collaborate across teams and work autonomously.
Intellectually curious, transparent, action-oriented, and kind (this is important!)
Compensation & Rewards:
In the United States, the Base compensation range for this role is USD 174,986- USD 209,983. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here.
All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally.