Greenhouse ·
contractDirector, Analytics Engineering
Gitlab · Remote, United States
GitLab provides an intelligent orchestration platform for DevSecOps, helping organizations boost developer productivity, improve operational efficiency, lower security and compliance risk, and speed digital transformation. As Director, Analytics Engineering, you would lead a team of eight and report to the VP of Data & Insights. The role centers on creating a trusted, AI‑ready self‑service layer: designing a governed semantic model with clear metrics and business definitions, building evaluation and ground‑truth datasets to measure answer quality, and instrumenting telemetry to track usage and pain points. You would also define how GitLab accesses data across BI tools, Claude, MCP servers, and Slack agents, set standards for data applications that combine Snowflake data, APIs, AI, and write‑back capabilities, and establish engineering practices for security, testing, deployment, and monitoring. Additionally, you would shape the long‑range roadmap, manage vendor and tool evaluations, and hire, coach, and retain a high‑performing analytics engineering team.
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 urgent stakeholder needs with investment in reusable data products and tech-debt reduction Hire, coach, and retain a high-performing team of 8: build career paths, develop leaders, distribute ownership, and recognize great work Act as customer zero for GitLab and GitLab Duo in data workflows, sharing feedback with Product and Engineering What you'll bring 12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads Deep expertise in data modeling and semantic layers (e.g., dbt Semantic Layer, Snowflake semantic views, LookML, Cube), and expert dbt, including testing and CI/CD across a multi-team project Hands-on experience building LLM-powered data access (text-to-SQL, agents, MCP servers), including evals and telemetry for answer quality, and advanced use of AI coding agents such as Claude Code Expert SQL and strong Snowflake experience; working knowledge of Python Strong data governance experience: data quality, lineage, certified datasets, and access controls (RBAC, row access and masking policies) Track record of leading cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and
| Role | Director, Analytics Engineering |
|---|---|
| Company | Gitlab |
| Location | Remote, United States |
| Type | contract |
| Compensation | Not disclosed |
| Posted | 2026-10-13 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4Director, Analytics Engineering at Gitlab: frequently asked questions
- What is the salary for this role?
- Gitlab has not stated compensation in the listing. Check the original posting or ask during the application process.
- Is the Director, Analytics Engineering position remote, hybrid or onsite?
- The listing marks this role as remote, with Remote, United States as the location.
- What is the application deadline?
- Gitlab has not listed a fixed deadline, so apply early in case the opening is filled.
- How do I apply for the Director, Analytics Engineering role?
- Use the Apply button on this page. It opens the original listing on job-boards.greenhouse.io, where you submit your application with the company.
More at Gitlab
Other jobs at Gitlab
- Intermediate Fullstack Engineer (ruby/vue.js), Growth · Remote, United Kingdom
- Engineering Manager, Tenant Scale: Gitaly · Remote, United Kingdom
- Senior Engagement Manager - EMEA · Remote Ireland; Remote, Germany; Remote, Spain; Remote, United Kingdom
- Staff Product Manager, Agentic Planning · Remote, United States
- Major Account Executive, Financial Services - US East · Remote, United States
Explore Related Placements
// similar opportunities
You might also like
Analytics Engineer
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the intern...
Director, FP&A
Gitlab
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency,...
Senior Analytics Engineer
Vestiairecollective
Vestiaire Collective is the leading global platform for desirable pre-loved fashion and a pioneer in transforming how people consume fashion. Our mission is sim...
Senior Analytics Engineer
Asana
Senior Analytics Engineer The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacin...
Solutions Architect - SLED (east)
Gitlab
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency,...
Engineering Manager
Aqemia
About AQEMIA AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is...