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 definitionsBuild evals, datasets, and telemetry for answer qualityDefine AI data access, BI,



and self-service strategiesBuild production data applications combining Snowflake, APIs, and AIHire, coach, and retain a high-performing team of eightRequirements:

12+ years in analytics engineering, data engineering, or BI5+ years leading teams and 2+ managing managers or senior leadsExpert dbt, SQL, Snowflake, and data modeling expertiseExperience building LLM-powered data access with evalsAbility to thrive in GitLab's all-remote asynchronous companyShape GitLab's AI-ready data foundation through analytics engineering leadership, semantic modeling, Snowflake, and trusted self-service.

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