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 (Winnipeg)
🏢 GitLab
📍 Winnipeg