Jobs / United States / GitLab B.V.
Director, Analytics Engineering
GitLab B.V. · 🇺🇸 Remote, United States · Remote
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer does not appear with approvals in the government data SponsorApply holds.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Why not apply?
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
SponsorApply flags time-wasters so your applications go where they can land. These come from the posting's own wording — read the original listing to confirm. See better-fit alternatives →
Sponsor Radar — GitLab B.V.
This employer does not appear with approvals in the government data SponsorApply holds.
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for GitLab B.V. →
About the role
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Director, Analytics Engineering, you'll lead a team of 8 and report to the VP of Data & Insights. You set direction across the data organization, stay close enough to the work to guide technical decisions credibly, and partner with Data Engineering, Data Science, IT, and business leaders. You will have three mandates: • Build trusted, AI-ready self-service. Deliver a semantic model that answers business questions correctly, with the telemetry, evals, and model flexibility to prove it and keep costs in check. • Set the strategy for how GitLab accesses data. Own the data models, BI tools, and AI access patterns (Claude, MCP servers, Slack agents) that put trusted data in everyone's hands. • Build data applications the whole company relies on. Ship production-grade apps that combine trusted data, APIs, and AI to answer questions dashboards can't. What you'll do • Build and own a trusted semantic model, with governed metrics and business definitions, that answers business questions consistently across every tool • Build evals and ground-truth datasets that measure answer quality, and use them to drive improvements and catch regressions • Instrument telemetry to see who uses the semantic model and AI tools, what they ask, and where they get stuck • Build a model-selection harness so GitLab can route work across LLMs and stay flexible on cost and quality • Own data modeling and curated datasets for self-service, with the ownership, data contracts, testing, and documentation that make them AI-ready • Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with the governance and security to keep access trusted and reliable • Own the enterprise BI and self-service tools strategy (e.g., Tableau, Omni), including evaluation, adoption, and cost • Build self-service capabilities, such as Claude skills, documentation, and guided workflows, that help people find and use data on their own • Build and own company-wide data applications, from Claude-built single-page apps to apps inside BI tools, that combine Snowflake data, API calls, AI-powered deep dives, and write-back to Postgres or Snowflake • Set engineering standards for data apps (security, authentication, testing, deployment, and monitoring) so they're reliable at company scale • Set a long-range roadmap tied to company strategy, and a lightweight operating model that balances