Intermediate Fullstack Engineer - Data Products

An overview of this role

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

You'll work across the stack, contributing to frontend experiences, backend services, APIs, and AI-enabled workflows. This is a hands-on product engineering role. You'll develop features, learn how we build and operate large-scale data systems, and work closely with Senior and Staff Engineers to deliver secure, reliable, and performant solutions.

We don't expect you to have all the answers, but we do expect you to ask questions, take ownership of your work, and make progress through ambiguity.

What you’ll do

• Develop well-scoped features, with support from Senior and Staff Engineers, for how GitLab and third-party data is ingested, modeled, and synced into the knowledge graph, meeting team goals for data freshness, sync reliability, and graph coverage.
• Build parts of integrations with external systems for business context, including Jira, observability tools, Zendesk, and ServiceNow, increasing indexed business context while meeting team goals for data completeness and freshness in the graph.
• Build features for the Software Engineering Intelligence dashboards, including DORA, value stream reporting, GitLab Duo, and software development lifecycle metrics rolled up across organizational structures, meeting team goals for reporting accuracy, performance, and coverage.
• Contribute to design discussions and technical direction for your features, with guidance from Senior and Staff Engineers, helping deliver secure, reliable, and performant solutions on schedule.
• Raise blockers and risks early, and work with Senior Engineers to unblock your work so milestones stay on track and delivery risk is reduced.
• Participate in design review and code review, and apply feedback to improve code quality, maintainability, and delivery velocity.
• Build a deep understanding of the system, including the data model and the platform the team builds on, so you can ship changes more independently and resolve issues faster.

What you’ll bring

• You find the owner, clarify the path, make the tradeoff, build the first version, and keep pushing until the work lands.
• Deep production experience building and operating fullstack applications.
• Hands-on fullstack proficiency with Go, Ruby, and Node.
• Experience with data platforms such as ClickHouse or comparable OLAP systems, including data modeling and query optimization.
• Hands-on experience building AI-powered product features.
• Experience operating multi-tenant applications across software as a service and self-managed environments.
• High velocity with sound judgment, strong written communication, and the ability to decompose complex initiatives into shippable milestones while creating alignment across stakeholders in an async-first environment.
• Experience building third-party or API integrations.

About the team

Data Products works across three surfaces:

• Dashboard and Reporting Framework
  Builds AI-native dashboard components so customers and internal teams can see engineering health and GitLab's impact across DORA, value stream reporting, AI impact, software development lifecycle trends, security, and quality, and launch their own custom dashboards on the same framework.
• Internal Ingestion
  Ingests third-party data into GitLab and powers tools like the knowledge graph, building integrations so that signals from systems like Jira, Zendesk, ServiceNow, and observability tools become one queryable, near-real-time graph of the developer ecosystem.
• External Ingestion
  Makes GitLab and knowledge graph data consumable outside the product through marketplace listings, data access APIs and software development kits, and co-branded partner products.

We are a team in a highly ambiguous, high-impact space, and we need engineers who can create clarity while building, make practical tradeoffs, unblock cross-team work, and keep pushing until meaningful customer value lands.