Director, Analytics Engineering

Details

GitLab is seeking a Director, Analytics Engineering to lead a team of 8 and report to the VP of Data & Insights. The role sets direction across the data organization, guides technical decisions, and partners with Data Engineering, Data Science, IT, and business leaders.

The role has three primary mandates: build trusted, AI-ready self-service through a governed semantic model; set GitLab's strategy for data access across data models, BI tools, and AI access patterns; and build production-grade data applications that combine trusted data, APIs, and AI.

Responsibilities

• Build and own a trusted semantic model with governed metrics and business definitions.
• Build evaluation systems and ground-truth datasets to measure answer quality, drive improvements, and catch regressions.
• Instrument telemetry to understand usage of semantic models and AI tools, user questions, and points of friction.
• Build a model-selection harness to route work across large language models and balance 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, with appropriate governance and security.
• Own the enterprise BI and self-service tools strategy, including evaluation, adoption, and cost management for tools such as Tableau and Omni.
• Build self-service capabilities such as Claude skills, documentation, and guided workflows.
• Build and own company-wide data applications, including Claude-built single-page applications and applications inside BI tools, combining Snowflake data, API calls, AI-powered deep dives, and write-back to Postgres or Snowflake.
• Establish engineering standards for data applications, including security, authentication, testing, deployment, and monitoring.
• Set a long-range roadmap aligned with company strategy and establish an operating model balancing urgent stakeholder needs with reusable data products and technical debt reduction.
• Hire, coach, and retain a high-performing team of 8; build career paths, develop leaders, distribute ownership, and recognize strong performance.
• Act as customer zero for GitLab and GitLab Duo in data workflows and share feedback with Product and Engineering.

Requirements

• 12+ years of experience in analytics engineering, data engineering, or BI.
• 5+ years leading teams and 2+ years managing managers or senior leads.
• Deep expertise in data modeling and semantic layers, such as dbt Semantic Layer, Snowflake semantic views, LookML, or Cube.
• Expert-level dbt experience, including testing and CI/CD across a multi-team project.
• Hands-on experience building LLM-powered data access, including text-to-SQL, agents, and MCP servers, with evaluations and telemetry for answer quality.
• Advanced use of AI coding agents such as Claude Code.
• Expert SQL and strong Snowflake experience, with working knowledge of Python.
• Strong data governance experience, including data quality, lineage, certified datasets, access controls, RBAC, row access policies, and masking policies.
• Track record of leading cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and self-service at scale.
• Systems-thinking ability to connect models, pipelines, and architecture decisions and design for second-order effects.
• Exceptional communication skills, including writing clear technical specifications, setting a clear vision, making trade-offs visible, and influencing executives and peers.
• Ability to make pragmatic decisions amid ambiguity and deliver the right next version of emerging technology.
• Ability to use GitLab, work effectively 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.
• Experience with Tableau, Omni, or a BI platform migration.
• Experience with web application development, such as React and TypeScript, and Postgres.
• Experience owning finance or revenue-critical data, such as ARR or consumption data, where accuracy and auditability are essential.

Team

Analytics Engineering makes GitLab's data trusted, easy to find, and ready for anyone to use through dashboards, Claude, or Slack agents. The team owns curated data models, the semantic layer, self-service tools, and data applications that enable teams to answer their own questions.

Compensation and Benefits

The United States base salary range is $139,200-$285,600 USD. The range does not include bonuses, equity, or benefits. Benefits include flexible paid time off, team member resource groups, equity compensation and an employee stock purchase plan, a growth and development fund, parental leave, and health, financial, and well-being support.

All GitLab roles are remote, although some roles may have location-based eligibility requirements. GitLab is an equal opportunity workplace and provides reasonable accommodations during the recruiting process.