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.

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