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