Director, Analytics Engineering

🕒 October 13

🇺🇸 United States – Remote

💵 $139.2k - $285.6k / year

⏰ Full Time

🔴 Lead

📊 Analytics Engineer

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GitLab is the most comprehensive AI-powered DevSecOps platform, offering tools for automated software delivery, security, and compliance throughout the software development lifecycle. It provides solutions across areas such as AI-assisted development, continuous integration/continuous deployment (CI/CD), source code management, and vulnerability management. GitLab aims to simplify and accelerate software delivery by uniting development, security, and operations on a unified platform. It is particularly recognized for its AI code assistants and has been named a leader in the Gartner Magic Quadrant™ for DevOps Platforms, making it a preferred choice for many enterprises.

📋 Description

• Lead a team of 8 and report to the VP of Data & Insights • Set direction across the data organization and guide technical decisions • Partner with Data Engineering, Data Science, IT, and business leaders • Build and own a trusted semantic model with governed metrics and business definitions • Build evaluation datasets and ground-truth datasets to measure answer quality and catch regressions • Instrument telemetry for semantic model and AI tool usage • Build a model-selection harness to route work across LLMs and manage cost and quality • Own data modeling and curated datasets for self-service, including ownership, data contracts, testing, and documentation • Define the AI data access strategy across BI, Claude, MCP servers, and Slack agents • Own enterprise BI and self-service tools strategy, including evaluation, adoption, and cost • Build self-service capabilities such as Claude skills, documentation, and guided workflows • Build company-wide data applications combining Snowflake data, APIs, AI-powered analysis, and write-back to Postgres or Snowflake • Set engineering standards for data application security, authentication, testing, deployment, and monitoring • Set a long-range roadmap and operating model aligned with company strategy • Hire, coach, and retain a high-performing team of 8 • Act as customer zero for GitLab and GitLab Duo in data workflows and share feedback with Product and Engineering

🎯 Requirements

• 12+ years in analytics engineering, data engineering, or BI • 5+ years leading teams • 2+ years managing managers or senior leads • Deep expertise in data modeling and semantic layers, including dbt Semantic Layer, Snowflake semantic views, LookML, or Cube • Expert dbt, including testing and CI/CD across a multi-team project • Hands-on experience building LLM-powered data access, including text-to-SQL, agents, MCP servers, evals, and telemetry for answer quality • Advanced use of AI coding agents such as Claude Code • Expert SQL and strong Snowflake experience • Working knowledge of Python • Strong data governance experience, including data quality, lineage, certified datasets, and access controls such as RBAC, row access, and masking policies • Track record of leading cross-functional data initiatives from strategy through adoption and measurable business impact • Experience with enterprise BI and self-service at scale • Ability to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values • Nice to have: experience with LLM routing or gateway tools and managing model costs • Nice to have: experience with Tableau, Omni, or a BI platform migration • Nice to have: experience with web app development, such as React and TypeScript, and Postgres • Nice to have: experience owning finance or revenue-critical data

🏖️ Benefits

• Benefits to support your health, finances, and well-being • Flexible Paid Time Off • Team Member Resource Groups • Equity Compensation & Employee Stock Purchase Plan • Growth and Development Fund • Parental Leave • All roles are remote • AI as a core productivity multiplier and daily workflow support

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