Senior Backend Engineer - Databases - Analytics

The Opportunity

Grafana Labs is building observability tools that help users understand, respond to, and improve their systems regardless of scale, complexity, or tech stack. As part of a new skunkworks initiative, we are creating an AI-native data intelligence system that gives AI agents and humans reliable, governed access to enterprise context.

We are looking for a Senior Software (Database) Engineer to help build the underlying storage system for our general-purpose data platform. The database layer features both OLAP and OTLP capabilities to support classic analytics queries while serving freshly stored data, embracing the separation of compute and storage.

What You'll Be Doing

• Database Architecture: Design, implement, test, and operate ingestion, query planning, distributed query execution, data formats, and storage formats.
• Scalable SaaS Foundation: Define and build the architecture for a multi-tenant database service, including tenant isolation, usage tracking, quotas, audit logs, and background jobs.
• Agent-Facing Retrieval: Build APIs and database interfaces allowing AI agents, MCP tools, CLIs, and internal apps to retrieve data quickly.
• End-to-End Ownership: Instrument database services with metrics, logs, traces, and dashboards, operating what you build from prototype to production.
• Technical Direction: Shape the architecture, service boundaries, storage choices, API contracts, and engineering practices.

What Makes You a Great Fit

• Strong engineering skills with experience building production-grade, user-facing software systems.
• Practical experience with AI technologies and frameworks.
• Comfort with quick iteration, experimentation, and working through ambiguity.
• Mastery of a programming language like Golang, C++, or Rust.
• Solid background in distributed systems, catalogs, table formats, and query engines.
• Cloud-native experience (AWS, GCP, Azure).

Bonus Points

• Experience building distributed query engines.
• Experience building data warehouses and/or data lakes.
• Experience building tools for data engineering.