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Salary: USD 139,200 - 285,600 / annual
GitLab is seeking a Director of Analytics Engineering to lead a team of 8 and report to the VP of Data & Insights. You will 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 have three core mandates:
1. 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.
2. 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.
3. 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.
Key responsibilities include:
- Build and own a trusted semantic model with governed metrics and business definitions that answer business questions consistently across every tool
- Build evals and ground-truth datasets that measure answer quality and drive improvements
- 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 ownership, data contracts, testing, and documentation
- Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with governance and security
- Own 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
- Build and own company-wide data applications that combine Snowflake data, API calls, AI-powered deep dives, and write-back capabilities
- Set engineering standards for data apps (security, authentication, testing, deployment, monitoring)
- Set a long-range roadmap tied to company strategy and a lightweight operating model
- Hire, coach, and retain a high-performing team of 8; build career paths and develop leaders
- Act as customer zero for GitLab and GitLab Duo in data workflows
GitLab is the intelligent orchestration platform for DevSecOps, trusted by more than 50 million registered users and over 50% of the Fortune 100. The company embraces AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows.
REQUIREMENTS:
- 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 multi-team projects
- 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 self-service at scale
- Systems thinker who sees how models, pipelines, and architecture decisions connect
- Exceptional communicator who writes clear technical specs, sets clear vision, makes trade-offs visible, and influences executives and peers
- Pragmatic in ambiguity: makes sound decisions on emerging technology and ships the right next version
- Able to use GitLab, thrive in an all-remote, asynchronous company, and work in line with GitLab's values
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 (e.g., React, TypeScript) and Postgres
- Experience owning finance or revenue-critical data (e.g., ARR, consumption) where accuracy and auditability are non-negotiable
