Senior Backend Engineer - Databases - Analytics | Spain | Remote

grafanalabs; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Fully remote position

Equity-based compensation

Generous annual leave (around 30 days)

In-person onboarding

Job summary

grafanalabs is seeking a senior backend engineer to build the storage and database layers for an analytics platform that blends OLAP queries with low-latency telemetry ingestion. The role underpins an AI-native data intelligence system designed for enterprise governance, with a multi-tenant SaaS maturity pathway.

You will shape end-to-end database components, collaborate with product and infra, and ensure scalable, reliable operations across cloud providers as the system evolves to production.

Qualifications

• Senior-level experience designing and operating distributed database or storage systems.
• Familiarity with both OLAP and OLTP workloads, query planning, and distributed execution.
• Comfort working with separated compute and storage architectures on public cloud infrastructure.
• Ability to navigate ambiguity in an early-stage environment and make pragmatic architecture calls.
• A collaborative, feedback-oriented approach to cross-functional work.

Responsibilities

• Own parts of the database end-to-end: design, implement, test, and operate ingestion pipelines, query planners, distributed query execution, data formats, and on-disk storage formats.
• Help shape a multi-tenant SaaS foundation, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
• Build APIs and database interfaces that let AI agents, MCP tools, CLIs, and internal applications retrieve governed data quickly and consistently.
• Make pragmatic trade-offs between fast experimentation and long-term reliability as the system moves from internal dogfooding to production.
• Partner with product and infrastructure teammates on architectural decisions that support running across multiple cloud providers with separated compute and storage.

Job description

Role overview

A senior backend engineer is needed to build the storage and database layer for an analytics platform that blends classic OLAP queries with low-latency, telemetry-style ingestion. The work underpins an AI-native data intelligence system designed to give AI agents reliable, governed access to enterprise context, and the team operates with high autonomy from early prototyping through to multi-tenant SaaS maturity.

Responsibilities

• Own parts of the database end-to-end: design, implement, test, and operate ingestion pipelines, query planners, distributed query execution, data formats, and on-disk storage formats.
• Help shape a multi-tenant SaaS foundation, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries.
• Build APIs and database interfaces that let AI agents, MCP tools, CLIs, and internal applications retrieve governed data quickly and consistently.
• Make pragmatic trade-offs between fast experimentation and long-term reliability as the system moves from internal dogfooding to production.
• Partner with product and infrastructure teammates on architectural decisions that support running across multiple cloud providers with separated compute and storage.

Requirements

• Senior-level experience designing and operating distributed database or storage systems.
• Familiarity with both OLAP and OLTP-style workloads, query planning, and distributed execution.
• Comfort working with separated compute and storage architectures on public cloud infrastructure.
• Ability to navigate ambiguity in an early-stage environment and make pragmatic architecture calls.
• A collaborative, feedback-oriented approach to cross-functional work.

Nice to have

• Background taking systems from internal prototype to production-grade SaaS.
• Interest in agent-facing retrieval, metadata, lineage, or data-quality tooling.

Benefits and work setup

• Fully remote position with team members distributed across many countries.
• Equity-based compensation intended to align long-term outcomes as the organization scales.
• Generous annual leave policy (around 30 days per year) plus reserved shutdown days for team-wide rest, with local legal compliance.
• In-person onboarding at the start of employment to accelerate ramp-up.