Lead analytics engineering at GitLab with dbt, Snowflake, and AI-ready data models in an all-remote, asynchronous company. Guide trusted self-service across the organization.

As Director, Analytics Engineering, you will lead eight team members and report to the VP of Data & Insights. You will set data organization direction while guiding technical decisions and partnering with Data Engineering, Data Science, IT, and business leaders. The work spans semantic models, LLM-powered data access, BI strategy, and production data applications.

Key Responsibilities:

- Own governed semantic models and consistent business definitions
- Build evals, datasets, and telemetry for answer quality
- Define AI data access, BI, and self-service strategies




- Build production data applications combining Snowflake, APIs, and AI
- Hire, coach, and retain a high-performing team of eight

Requirements:

- 12+ years in analytics engineering, data engineering, or BI
- 5+ years leading teams and 2+ managing managers or senior leads
- Expert dbt, SQL, Snowflake, and data modeling expertise
- Experience building LLM-powered data access with evals
- Ability to thrive in GitLab's all-remote asynchronous company

Shape GitLab's AI-ready data foundation through analytics engineering leadership, semantic modeling, Snowflake, and trusted self-service.

📌 Director Analytics Engineering AI Data (Canada)
🏢 GitLab
📍 Canada