Staff Data Analyst at GitLab, Bengaluru

Staff data analyst at GitLab Bengaluru, owning annual operating plan modeling, capacity planning and team-performance scorecards.

This full-time Bengaluru role was posted on 1 October 2026. The listing describes owning annual operating plan and capacity planning through data modeling and validation that supports workforce and budget decisions, and building and maintaining utilization and team-performance scorecards including automated alerting that surfaces trends. Requirements include experience as a business intelligence analyst, analytics engineer or similar data role, ideally in a software-as-a-service company, and experience partnering with Technical Support, Business Operations, Product Engineering or similar organizations.

About GitLab

GitLab builds a DevSecOps platform that covers source code management, CI/CD, security scanning and planning in a single application. Its listings state that more than 50 million registered users and more than half of the Fortune 100 use the platform.

GitLab operates as an all-remote company with team members in many countries, including India. Its public handbook and listing pages describe an asynchronous, documentation-heavy way of working, and its listings note that team members are expected to use AI tooling in daily workflows. Learn more on GitLab's website.

The role in plain terms

This is analytics at the operating-model level: your models feed headcount, budget and capacity decisions, which is staff-level influence through data rather than dashboard production. The automated-alerting expectation shows the team wants self-serve, proactive analytics, not request-response reporting. The partner list - Support, Business Operations, Product Engineering - spans technical and business orgs, so translating between them is part of the craft.

The team and the work

Per the listing, the work supports workforce and budget planning with data modeling and validation. GitLab's all-remote, documentation-heavy culture favors analysts who write things down and build for async consumption.

What the employer asks for

These requirements are quoted from the employer's listing, kept in their exact words so eligibility details are not distorted:

Experience as a business intelligence analyst, analytics engineer, or in a similar data role, ideally in a software as a service or technology company.
Experience partnering with Technical Support, Business Operations, Product Engineering, or similar organizations.
Fluency in SQL, including complex multi-table joins, grouping and aggregation, common table expressions, and conditional filters.
Hands-on experience building dashboards and reports in Zendesk Explore, Tableau, Looker, or similar business intelligence tools.
Translate ambiguous business questions into structured analytical frameworks.
Present findings clearly to technical and non-technical stakeholders.
Plan and prioritize work independently in a remote, cross-functional environment across time zones.
You may also bring experience with large language model-based tools, artificial intelligence and machine learning workflows, durable data solutions, analytics frameworks, in-depth data analysis, or...

Who this role suits

Senior BI analysts or analytics engineers with workforce, capacity or operations analytics experience, ideally in SaaS. Not for product-analytics specialists - the domain is operational and financial planning.

Practical notes

For staff analytics roles, expect questions on a model you built that drove a real planning decision, plus technical SQL and modeling discussion. Experience with planning cycles (annual plans, capacity models) is the specific differentiator here.

Working at GitLab

Roles at GitLab span the product itself (backend in Ruby and Go, frontend, security, infrastructure) plus internal systems teams that build the company's own tooling and automations.

How to apply

Apply directly on the employer's site: Staff Data Analyst at GitLab. We found this listing on the Greenhouse public job board (job-boards.greenhouse.io), where it was posted on 1 Oct 2026 and was still open when we checked on 30 Oct 2026. Before applying, re-read the employer's own description in full, since eligibility details, deadlines and process steps can change at any time and the employer's page is always the final word. Tailor your resume to the specific requirements above rather than sending a generic one: mirror the skills and tools the listing names where you genuinely have them. A short, specific note on why this team and this problem interest you goes further than a long generic cover letter. Never pay a fee to apply or interview; genuine employers, including this one, do not charge candidates.

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