Director of Analytics Engineering

GitLab; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity compensation

Employee Stock Purchase Plan

Generous Paid Time Off

Job summary

GitLab is seeking a Director of Analytics Engineering to lead an 8-person team and partner with Data & Insights, Data Engineering, Data Science, IT, and business leaders. You will set the data strategy, own the semantic model, and deliver AI-ready self-service at scale.

You will guide data models, BI tools, and AI access patterns, build data applications, and drive governance, telemetry, and cost-conscious decision-making across the company.

Qualifications

• Expert SQL and Snowflake experience.
• Proven ability to lead cross-functional data initiatives.
• Strong data governance and RBAC experience.

Responsibilities

• Lead an 8-person Analytics Engineering team and align with Data & Insights.
• Define strategy for trusted data and AI-ready self-service.
• Own data models, BI tools, and AI access patterns across tools.

Skills

SQL

Snowflake

Python

dbt

Semantic Layer

Data Modeling

LLM Data Access

CI/CD

LookML

Data Governance

Tools

Snowflake

Tableau

Omni

LookML

PostgreSQL

dbt

Job description

• As Director, Analytics Engineering, you’ll lead a team of 8 and report to the VP of Data & Insights.
• You set direction across the data organization, stay close enough to the work to guide technical decisions credibly, and partner with Data Engineering, Data Science, IT, and business leaders
• You will have three mandates;
• Build trusted, AI-ready self-service. Deliver a semantic model that answers business questions correctly, with the telemetry, evals, and model flexibility to prove it and keep costs in check
• Set the strategy for how GitLab accesses data. Own the data models, BI tools, and AI access patterns (Claude, MCP servers, Slack agents) that put trusted data in everyone’s hands
• Build data applications the whole company relies on. Ship production-grade apps that combine trusted data, APIs, and AI to answer questions dashboards can’t
• Build and own a trusted semantic model, with governed metrics and business definitions, that answers business questions consistently across every tool
• Build evals and ground-truth datasets that measure answer quality, and use them to drive improvements and catch regressions
• Instrument telemetry to see who uses the semantic model and AI tools, what they ask, and where they get stuck
• Build a model-selection harness so GitLab can route work across LLMs and stay flexible on cost and quality
• Own data modeling and curated datasets for self-service, with the ownership, data contracts, testing, and documentation that make them AI-ready
• Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with the governance and security to keep access trusted and reliable
• Own the enterprise BI and self-service tools strategy (e.g., Tableau, Omni), including evaluation, adoption, and cost
• Build self-service capabilities, such as Claude skills, documentation, and guided workflows, that help people find and use data on their own
• Build and own company-wide data applications, from Claude-built single-page apps to apps inside BI tools, that combine Snowflake data, API calls, AI-powered deep dives, and write-back to Postgres or Snowflake
• Set engineering standards for data apps (security, authentication, testing, deployment, and monitoring) so they’re reliable at company scale
• Set a long-range roadmap tied to company strategy, and a lightweight operating model that balances urgent stakeholder needs with investment in reusable data products and tech-debt reduction
• Hire, coach, and retain a high-performing team of 8: build career paths, develop leaders, distribute ownership, and recognize great work
• Act as customer zero for GitLab and GitLab Duo in data workflows, sharing feedback with Product and Engineering

Benefits

• We offer benefits to manage your health, wealth, and well-being regardless of location
• Flexibility in schedule to be there for life's important moments
• Equity compensation & Employee Stock Purchase Plan offered
• Generous Paid Time Off

Expert SQL and strong Snowflake experience; working knowledge of Python12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leadsDeep expertise in data modeling and semantic layers (e.g., dbt Semantic Layer, Snowflake semantic views, LookML, Cube), and expert dbt, including testing and CI/CD across a multi-team projectAble to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's valuesHands-on experience building LLM-powered data access (text-to-SQL, agents, MCP servers), including evals and telemetry for answer quality, and advanced use of AI coding agents such as Claude CodeSystems thinker who sees how models, pipelines, and architecture decisions connect, and designs for second-order effectsTrack record of leading cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and self-service at scaleExceptional communicator who writes clear technical specs, sets a clear vision, makes trade-offs visible, and influences executives and peers across the companyPragmatic in ambiguity: makes sound decisions on emerging technology and ships the right next version rather than waiting for the ideal end stateStrong data governance experience: data quality, lineage, certified datasets, and access controls (RBAC, row access and masking policies)Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirementExperience with web app development (e.g., React, TypeScript) and PostgresExperience owning finance or revenue-critical data (e.g., ARR, consumption) where accuracy and auditability are non-negotiableExperience with LLM routing or gateway tools and managing model costsExperience with Tableau, Omni, or a BI platform migration