Staff Fullstack Engineer, Data Products
New
G
GitLabDevSecOps software
Remote, Canada; Remote, United StatesFull-TimeStaff
Salary152,800 - 259,200 USD per year
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Job Details
- Required Skills
- Node.jsRubyGoSaaS
Requirements
- Demonstrate the ability to influence as a Staff engineer, owning product or platform systems end to end across multiple engineering and product teams.
- Bring high agency: find owners, clarify paths, make decisions, and keep work moving through delivery.
- Raise the people and codebase around you as a force multiplier.
- Bring deep full-stack expertise, including strong proficiency in Go, Ruby, and Node.
- Have depth in at least one of analytics and metrics platforms, graph data systems, or CDC and warehouse integration.
- Have hands-on experience building production AI-powered tool orchestration.
- Have experience operating multi-tenant systems across SaaS and self-managed deployments.
- Communicate directly and build alignment across teams.
- Write things down and make reasoning legible.
Responsibilities
- 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, including Jira, observability tools, Zendesk, and ServiceNow, and index business context into the graph.
- Architect the Data Marketplace so customers can consume GitLab data through Snowflake, Databricks, and BigQuery without 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 with Product, Design, and the graph backend team.
- Resolve cross-team dependencies across graph backend, AI Platform, and Infrastructure.
- Mentor senior and intermediate engineers through design reviews, pairing, and code review.
- Identify systemic bottlenecks, simplify processes, and design systems to improve execution velocity.
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