Director, Analytics Engineering

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GitLabAnalytics engineering

Listing locations: USAFull-TimeDirector

Salary139,200 - 285,600 USD per year

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Job Details

Experience: 12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads
Required Skills: PythonSQLSnowflakeData modelingdbt

Bring 12+ years in analytics engineering, data engineering, or BI.
Have 5+ years leading teams and 2+ years managing managers or senior leads.
Demonstrate deep expertise in data modeling and semantic layers, such as dbt Semantic Layer, Snowflake semantic views, LookML, or Cube.
Have expert dbt experience, including testing and CI/CD across a multi-team project.
Have hands-on experience building LLM-powered data access, including text-to-SQL, agents, or MCP servers, with evaluations and telemetry.
Have advanced experience using AI coding agents such as Claude Code.
Have expert SQL skills, strong Snowflake experience, and working knowledge of Python.
Have strong data governance experience, including data quality, lineage, certified datasets, and access controls such as RBAC and row access and masking policies.
Have led cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and self-service at scale.
Be able to use GitLab and work effectively in an all-remote, asynchronous company.

Build and own a trusted semantic model with governed metrics and business definitions.
Build evaluation datasets and telemetry to measure answer quality, usage, and regressions.
Develop a model-selection harness to route work across LLMs and manage cost and quality.
Own data modeling and curated datasets, including data contracts, testing, and documentation.
Define the AI data access strategy across BI, Claude, MCP servers, and Slack agents.
Own the enterprise BI and self-service tools strategy, including evaluation, adoption, and cost.
Build company-wide data applications combining Snowflake data, APIs, AI, and write-back to Postgres or Snowflake.
Set data-app engineering standards for security, authentication, testing, deployment, and monitoring.
Set the roadmap and operating model for stakeholder needs, reusable data products, and technical-debt reduction.
Hire, coach, and retain an eight-person team, and act as customer zero for GitLab and GitLab Duo in data workflows.

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