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Senior Full Stack Engineer | Database Observability, Grafana Cloud | Germany | Remote

AI Summary
Grafana Labs seeks a senior full-stack engineer with a primary frontend focus for its Database Observability squad. The role involves building React and TypeScript experiences for exploring database telemetry, while contributing to Go services and APIs when needed. The engineer will own projects from discovery through rollout, use customer feedback to iterate, and participate in on-call and customer-escalation support. Close collaboration with product, design, backend engineering, and distributed open-source communities is central to the position. Candidates must be eligible to work remotely from the UK, Ireland, Spain, or Germany and attend in-person onboarding.
Remote from
UK, Spain, Germany+1 more, Ireland
Salary
EUR 100k–125k / yr
Employment
Full Time
Experience
Senior
Published
Apply before
6 Dec 2026
Listing views
20
Application actions
1
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Opportunity details

About this role.

Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X.

We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do.

You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity.

This is a remote opportunity and we would be interested in applications from the UK, Ireland, Spain and Germany.

About Grafana Cloud Observability

Grafana Cloud is our fully managed observability platform that integrates metrics, logs, and traces with Grafana. It allows our customers to use the best open source observability software, including Prometheus, Mimir, Loki, and Tempo, without the overhead of installing, maintaining and scaling their own observability stack.

Within the Observability department, we build products that help customers understand and troubleshoot their applications and infrastructure. We work closely with product management, design and other engineering squads to provide seamless and highly curated experiences for our customers.

The squad: Database Observability

We build and evolve Grafana Cloud Database Observability. We want to help users understand the health and performance of their databases, identify slow queries and troubleshoot issues through clear, actionable insights.

As a frontend engineer on the squad, you’ll build experiences that make complex database telemetry easy to explore and understand. You’ll work closely with backend engineers, product management and design to take ideas from early exploration through to production and improve them based on customer feedback.

Our frontend stack is primarily TypeScript and React, interacting with backends written in Go. Your primary focus will be frontend engineering, with opportunities to work across the stack, contributing to APIs and backend functionality to deliver complete customer experiences. Frontend engineers at Grafana also have opportunities to contribute to open source communities.

The opportunity:

  • Own technical projects from problem framing through rollout, including getting user feedback and measuring whether what you shipped actually worked.
  • Collaborate with Product Management, Product Design and backend engineers to build intuitive user experiences using clean, reusable components, contributing to supporting APIs and backend functionality where needed.
  • Mentor and collaborate with other engineers. Raise the engineering bar through code review, design feedback, pairing on hard problems, and writing that leaves the team better than you found it.
  • Participate in on-call for the software you help build, contributing to incident response and learning from incidents.
  • Provide technical support in customer escalations and help us identify areas of high friction to address.
  • Collaborate with other squads on shared dependencies, contribute to design proposals, and share the team’s work through demos and technical discussions.

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 with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google.

What makes you a great fit:

  • We highly value those who are intellectually curious, who default to transparency, possess a high bias towards action, and who are also kind and enjoy working as a team.
  • Strong frontend engineering experience, with experience across the stack. You have experience building and maintaining production web applications with React and TypeScript, and are comfortable contributing to backend services and APIs. You value maintainability, readability, automated testing and secure development practices.
  • Technical ownership. You have solid experience delivering complex projects, mentoring other engineers and helping teammates work more effectively. You communicate clearly in a fully remote, asynchronous environment.
  • You take responsibility for operating the software you have built. You have experience being on-call, supporting software in production, ensuring reliability and responding to incidents as needed.
  • You enjoy working on complex solutions, building production software systems. You’re a self-starter, capable of tackling complex engineering problems with minimal supervision.
  • User focus and pragmatism. You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate.
  • AI experience with a practical mindset. You use AI coding tools thoughtfully to improve productivity and quality, validate their output, and share useful practices with teammates.
  • You care about our community of users and contributors and are keen to be an active Grafana Community Contributor.

Bonus Points for

  • Open-source contribution or maintainership, and comfort engaging a community in the open.
  • An active interest in observability (metrics, logs and traces) and experience with tools like Grafana, Prometheus or other observability platforms.
  • Experience with databases, SQL or database performance monitoring.
  • Experience building backend services in Go.
  • Experience as an on-call user of Grafana, Prometheus, Loki or Tempo in a previous role (or on a homelab).
  • Experience in a fully remote, globally distributed team.

Compensation & Rewards:

In Germany, the base compensation range for this role is €100,000 – €125,000. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. 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.

*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process.

Why You’ll Thrive at Grafana Labs:

  • 100% Remote, Global Culture – As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose.
  • Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment.
  • Transparent Communication – Expect open decision-making and regular company-wide updates.
  • Innovation-Driven – Autonomy and support to ship great work and try new things.
  • Open Source Roots – Built on community-driven values that shape how we work.
  • Empowered Teams – High trust, low ego culture that values outcomes over optics.
  • Career Growth Pathways – Defined opportunities to grow and develop your career.
  • Approachable Leadership – Transparent execs who are involved, visible, and human.
  • Passionate People – Join a team of smart, supportive folks who care deeply about what they do.
  • In-Person onboarding – We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.
  • Balance is Key – We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable.

Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow.

Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings.

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Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightЭто сложная senior-позиция, сочетающая разработку пользовательских интерфейсов, вклад в бэкенд, эксплуатацию production-систем и работу с инцидентами. Требуются самостоятельное техническое лидерство, наставничество и уверенная работа с observability и распределённой командой.

Salary analysis

Estimated compensation compared with the broader EU market for similar roles.

Estimated job median (per year)Market rate
€112,500
EU market range (per year)€95k–€135k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. Работодатель указывает базовую компенсацию €100,000–€125,000 в Германии. Годовой период выведен из масштаба указанной базовой оплаты и контекста senior full-time роли, поскольку в объявлении он прямо не назван. Оценочный рыночный диапазон для senior full-stack инженера в Германии с опытом React, TypeScript, Go и observability составляет €95,000–€135,000 в год; RSU не включены в базовую оплату.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a React interface for investigating a slow database query while keeping the experience understandable for users with different levels of expertise?

I would begin with the user’s investigation workflow and prioritize the key signals: query latency, frequency, resource impact, and time range. I would provide a clear summary first, then progressively disclose detailed query plans, dimensions, and correlated metrics. Reusable TypeScript components, accessible visual states, URL-persisted filters, and performance-aware data loading would make the experience consistent and scalable.

Describe how you would contribute across the frontend and Go backend when delivering a new observability feature.

I would align early with product and design on user outcomes, define API contracts with backend engineers, and identify ownership boundaries. On the frontend I would implement typed data access, resilient loading and error states, and tests; where appropriate, I would contribute Go handlers or API changes with validation, authorization, observability, and backward compatibility in mind. I would ship incrementally behind a feature flag, monitor adoption and reliability, and iterate from user feedback.

Tell us about your approach to being on-call for software you helped build.

I treat on-call as part of product ownership. I ensure actionable alerts, dashboards, runbooks, and safe rollback paths exist before launch, then respond methodically during incidents by assessing impact, mitigating quickly, communicating clearly, and documenting decisions. Afterward, I participate in blameless follow-up work that addresses root causes and improves detection, resilience, and the operator experience.

How do you use AI coding assistants while maintaining engineering quality and security?

I use AI tools to accelerate repetitive work such as test scaffolding, documentation drafts, refactoring options, and exploratory prototypes. I validate generated output against requirements, security practices, project conventions, and automated tests rather than accepting it blindly. Code review, small changes, and careful handling of sensitive data remain essential safeguards.

How would you mentor engineers and raise the technical bar in an asynchronous remote team?

I would provide timely, specific code-review feedback that explains trade-offs and teaches principles instead of merely requesting changes. I would pair on difficult problems, write concise design proposals and decision records, and create reusable examples or documentation for recurring patterns. I would also proactively make space for questions and recognize good engineering judgment to build trust across time zones.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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