GitLab

Director, Analytics Engineering

Work from home

Remote role where the employee must remain based in a particular country.

United States only

From the employer's advert: The base salary range for this role’s listed level is currently for residents of the United States only.

Employer listed it 12 days ago · Added 12 days ago

First listed 12 days ago and still open.

Salary

$139,200 to $285,600

Location

United States only

Work style

Async

Contract

Full-time

Experience

Lead

What the advert says

Quoted word for word from the employer's advert. Where it says nothing, we say so.

Working hours: Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values
Where you can work from: Location eligibility not confirmed
Contract: How GitLab Supports Full-Time Employees
Experience asked for: Not mentioned in the advert
Pay: The base salary range for this role’s listed level is currently for residents of the United States only.

Remote flexibility

Work from home

This is a remote role, but the employee must be based in United States. It is work from home rather than work from anywhere.

What the employer says

Source listing states candidate location: "Remote, United States, United States of America"
Job description states: "residents of the United States only. This range"

What Nomaders makes of it

Payroll and tax are likely handled in that country only

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

Before you apply

Questions worth asking: Nomaders interpretation

The advert does not say where you can be based. Ask which countries they can legally employ or contract you from.

Produced automatically from this advert's text; not reviewed by a person. The employer's own page is the final word.

About the role

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.

* Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.

An overview of this role

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.

What you'll do

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

What you'll bring

12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads

Requirements

·12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads
·Deep 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 project
·Hands-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 Code
·Expert SQL and strong Snowflake experience; working knowledge of Python
·Strong data governance experience: data quality, lineage, certified datasets, and access controls (RBAC, row access and masking policies)

Benefits

·Flexible Paid Time Off
·Team Member Resource Groups
·Equity Compensation & Employee Stock Purchase Plan
·Growth and Development Fund

How to apply

1Check the flexibility label above, work from home, matches where you plan to live and work.
2Tailor your CV to the role at GitLab, mentioning your remote working experience and working hours (Async).
3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 13d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.