Director, Analytics Engineering

📋 Description Build and own a trusted semantic model, with governed metrics and business definitions, that Build evals and ground-truth datasets that measure answer quality, and use them to drive Instrument telemetry to see who uses the semantic model and AI tools, what they ask, and where they Build a model-selection harness so GitLab can route work across LLMs and stay flexible on cost and Own data modeling and curated datasets for self-service, with the ownership, data contracts Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with the 🎯 Requirements 12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and Deep expertise in data modeling and semantic layers (e.g., dbt Semantic Layer, Snowflake semantic Hands-on experience building LLM-powered data access (text-to-SQL, agents, MCP servers), including Expert SQL and strong Snowflake experience; working knowledge of Python Strong data governance experience: data quality, lineage, certified datasets, and access controls Track record of leading cross-functional data initiatives from strategy through adoption and 🎁 Benefits Equity Compensation & Employee Stock Purchase Plan Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Growth and Development Fund Parental Leave