Staff Fullstack Engineer, Data Products (Golang / Node)

An overview of this role

Data Products integrates GitLab and third-party SDLC data, and builds the dashboards, APIs, and data products that turn it into trusted, interoperable intelligence for customers and internal teams.

This is a 0 to 1 team and we are hiring for a foundational engineering role. That means you bring technical leadership through ambiguity, helping figure out what to build, making the foundational design decisions, and keeping delivery moving while the picture is still forming. You own the full lifecycle of what ships and stand behind it.

What you'll bring

• Proven ability to influence as a Staff owning product or platform systems end to end across multiple engineering and product teams.
• High agency, i.e finds the owner, clarifies the path, makes the call, and keeps pushing until the work lands.
• Force multiplier and raise the people and the codebase around them
• Deep full-stack expertise, including strong proficiency in Go, Ruby and Node. 
• Depth in at least one of analytics and metrics platforms, graph data systems, CDC and warehouse integration.
• Hands-on experience building production AI-powered tool orchestration.
• Experience operating multi-tenant systems across SaaS and self-managed deployment.
• Direct communicator who builds alignment across teams.
• Bias to write things down and make reasoning legible.

What you'll own

• Architect how GitLab and third-party data is ingested, modeled, and synced into the knowledge graph as a near-real-time graph of the development ecosystem.
• Lead integration with external systems for business context (Jira, observability tools, Zendesk, ServiceNow), indexed into the graph.
• Architect the Data Marketplace so customers consume GitLab data through Snowflake, Databricks, and BigQuery with no engineering dependencies.
• Publish GitLab observability as OpenTelemetry and broker the data-sharing APIs.
• Define operational readiness for everything the team ships across GitLab.com, Dedicated, and Self-Managed.
• Translate an ambiguous 0 to 1 problem space into concrete, iterable roadmaps in partnership with Product, Design, and the graph backend team.
• Resolve cross-team dependencies across graph backend, AI Platform, and Infrastructure without escalating