Grafana Labs
Marketing Analytics Director | United States | Remote
$179K–$214K
United States (Remote) +1 · Remote · Director · Full-time · Posted Jul 1, 2026
- Location
- United States (Remote)
USA (Remote) - Experience
- 8+ years in Marketing Analytics, GTM Strategy, or Data Science; at least 2 years in a lead architect capacity. People management is not required.
- Education
- Bachelor's or Master's degree in a quantitative field is a bonus, not a stated requirement.
About the job
Leads marketing analytics strategy and architecture, building data systems, predictive models, and AI-enabled workflows to improve demand generation, marketing ROI, and Grafana adoption and retention.
What you'll do
- Partner with GTM leaders on forecasting, target-setting, and demand-generation strategy.
- Architect marketing data in Google BigQuery and develop attribution, marketing-mix, lifetime-value, and quality-scoring models.
- Deploy AI agents and automated workflows to monitor data quality, detect market signals, and support marketing decisions.
What they ask for
- 8+ years in Marketing Analytics, GTM Strategy, or Data Science, including at least 2 years in a lead architect capacity within a high-growth SaaS or PLG environment.
- Mastery of SQL and Python, with deep experience architecting data environments in Google BigQuery, Snowflake, or similar warehouses.
- Hands-on experience building and shipping agentic systems using Claude Code, MCP, or comparable tools, plus production evaluator or analytical quality systems.
- Hands-on automation experience with N8N, custom API orchestration, or MCP-based tooling.
Nice to have
- Advanced proficiency with Grafana, Looker, or Tableau; familiarity with Salesforce, marketing automation, and product-led data streams.
- Bachelor's or Master's degree in a quantitative field; MBA or MS in Data Science is a significant plus.
Pay
$178,503 - $214,203 USD OTE (base salary or total pay not specified)
Tools
Google BigQuery, Snowflake, SQL, Python, Claude Code, MCP, N8N, Grafana
AI focus
Build and deploy LLM-powered agents, evaluator systems, predictive scoring models, and automated workflows for data-quality monitoring, funnel analysis, and marketing decisions.
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