From the listing
About the role
GitLab is the intelligent orchestration platform for DevSecOps, enabling organizations to increase developer productivity, improve operational efficiency, and reduce security risk. The company embraces AI as a core productivity multiplier, expecting team members to incorporate AI into daily workflows to drive innovation.
As Director, Analytics Engineering, you will lead a team of 8 and report to the VP of Data & Insights. You will set direction across the data organization, partner with business leaders, and execute three primary mandates: building trusted AI-ready self-service, setting the strategy for data access, and shipping production-grade data applications.
The Analytics Engineering team makes GitLab's data trusted and easy to find through curated data models, semantic layers, and self-service tools. As AI changes how people access data, the team ensures answers provided by AI tools are correct, consistent, and measurable.
What you'll do
- Build and own a trusted semantic model with governed metrics and business definitions.
- Build evals and ground-truth datasets to measure and improve answer quality.
- Instrument telemetry to monitor semantic model and AI tool usage.
- Build a model-selection harness to route work across LLMs for cost and quality flexibility.
- Own data modeling, curated datasets, data contracts, and documentation for AI-readiness.
- Define the AI data access strategy across BI tools, Claude, MCP servers, and Slack agents.
- Own enterprise BI and self-service tools strategy, including evaluation and adoption of tools like Tableau and Omni.
- Build data applications that combine Snowflake data, API calls, and AI-powered deep dives.
- Set engineering standards for security, authentication, testing, and monitoring of data apps.
- Hire, coach, and develop a high-performing team of 8.
- Act as 'customer zero' for GitLab and GitLab Duo in data workflows.
What they're looking for
- 12+ years in analytics engineering, data engineering, or BI.
- 5+ years leading teams and 2+ years managing managers or senior leads.
- Deep expertise in data modeling and semantic layers such as dbt Semantic Layer, LookML, or Cube.
- Expert dbt skills, including testing and CI/CD across multi-team projects.
- Hands-on experience building LLM-powered data access like text-to-SQL or agents.
- Expert SQL and strong Snowflake experience.
- Working knowledge of Python.
- Strong data governance experience including data quality, lineage, and RBAC.
- Track record of leading cross-functional data initiatives from strategy through adoption.
- Ability to thrive in an all-remote, asynchronous company.
Nice to have
- Experience with LLM routing or gateway tools and managing model costs.
- Experience with Tableau, Omni, or a BI platform migration.
- Experience with web app development using React, TypeScript, and Postgres.
- Experience owning finance or revenue-critical data like ARR or consumption.
From the company page
Gitlab benefits
◉ Remote policy · in their words
“We've scaled as an asynchronous, no-office company that's consistently recognized as a great place to work.”
Pulled from their careers page · verified by Atlas
The hot takeJeff's read on Gitlab
GitLab has put more effort into their employee marketing and policies than 99.99% of the companies we've researched over the years. Seriously, their handbook is absolutely massive.
The ONLY thing that throws me off about them is an unclear statement about their stance on what "work from anywhere" actually means. They say:
"All-remote means that each individual in an organization is empowered to work and live where they are most fulfilled."
But they also say that hey need to have an entity in your home country in order to be hired, so I'd love to know if they have a list of the countries they will hire from.