Staff Data Analyst, BI & Analytics Lead (Remote)

GitLab; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible Paid Time Off

Equity Compensation

Employee Stock Purchase Plan

Growth and Development Fund

Parental Leave

Job summary

GitLab is seeking a Staff Data Analyst to turn raw data into actionable insights for GitLab's global Support Engineering team. You will design dashboards, reports, and data models that help leaders monitor performance, optimize costs, and improve customer outcomes in a fully remote environment.

You'll partner with Technical Support, Business Operations, and Product Engineering; translate ambiguous questions into structured analytics; and present findings to stakeholders across time zones.

Qualifications

• Experience as a business intelligence analyst or analytics engineer in a SaaS/tech company.

Responsibilities

• Own BI planning and capacity modeling to support workforce and budget decisions.
• Build utilization and team-performance scorecards with real-time alerts.
• Analyze Support Economics including cost-per-ticket modeling and self-service savings.
• Develop performance indexes and heatmaps to identify product areas using most support resources.
• Lead dashboarding for AI adoption and ROI, measuring business impact across Support Engineering.
• Deliver monthly business review telemetry and executive-ready reports.

Skills

BI analyst

Analytics engineer

Cross-functional collaboration

SQL

Zendesk Explore

Tableau

Looker

Data dashboards

Executive reporting

Data modeling

Tools

Zendesk Explore

Tableau

Looker

Job description

GitLab is seeking a Staff Data Analyst to turn raw data into actionable insights for GitLab's global Support Engineering team. You will design dashboards, reports, and data models that help leaders monitor performance, optimize costs, and improve customer outcomes in a fully remote environment.

You'll partner with Technical Support, Business Operations, and Product Engineering; translate ambiguous questions into structured analytics; and present findings to stakeholders across time zones.