Grafana Labs - Marketing Analytics Director | United States | Remote

• Strategic GTM Partnership: Serve as the primary strategic partner to the GTM Leadership team (VP of Demand Gen, VP of Regional and Events, Head of Marketing Ops, CMO, Revenue Operations, Sales leadership and more), translating complex data into a clear roadmap for demand generation and revenue growth. • Dual-Track Target Setting: Architect and own a sophisticated forecasting framework that balances top-of-funnel volume with high-intent lead quality, optimized for Grafana Cloud conversion and retention. • Predictive Modeling and ROI: Develop and maintain machine learning models (Attribution, MMM, LTV) to predict campaign impact and steer budget allocation toward the highest-ROI channels. • Data Warehouse Architecture: Oversee the structure of marketing data within Google BigQuery, ensuring a scalable single source of truth that connects product usage data with marketing touchpoints. • Causal Inference and Inflection Hunting: Move beyond descriptive analytics to perform causal inference and predictive trend analysis. When the data shows an anomaly, whether a 3-month spike, a regional dip, or a campaign that overperformed, isolate the window and dig in. • Executive Storytelling: Transform technical data outputs into clear, compelling narratives for the executive team and board. Deliver a succinct read and go deep where pushed. • Utilizing AI and Automation • Agentic Insights: Deploy LLM-powered agents (Claude Code, MCP-based tooling, or comparable) to monitor BigQuery datasets and automatically flag quality shifts in the funnel before they impact revenue. • Autonomous Workflows: Implement orchestration patterns (N8N, custom MCP servers, or equivalent) to build self-healing data pipelines and automated responses to market signals, such as automated spend shifts based on conversion anomalies. • Predictive Quality Scoring: Build and deploy AI-driven scoring models that separate high-value potential users from low-signal volume, helping Sales and Marketing prioritize effectively. • What Makes You a Great Fit • 8+ years in Marketing Analytics, GTM Strategy, or Data Science, with at least 2 years in a lead architect capacity (IC track or player-coach; people management not required) within a high-growth SaaS or PLG environment. • Demonstrated history as a force multiplier. You can point to specific tooling, rituals, evaluator systems, or frameworks you built that made other analysts or the broader org measurably better. A portfolio of dashboards you personally produced is not sufficient. • Data Science and Engineering: Mastery of SQL and Python required. Deep experience architecting data environments in Google BigQuery, Snowflake, or similar warehouses. • Hands-on AI fluency as a builder, not a user. You have built and shipped agentic systems with Claude Code, MCP, or comparable tools. You understand where LLMs fail and how to design around those limitations. You have built evaluator agents, prompt-grading systems, or analytical quality tooling in production. • Automation Proficiency: Hands-on experience building complex logic and integrations using N8N, custom API orchestration, or MCP-based tooling. • Visualization and BI: Advanced proficiency in modern data stack visualization tools (Grafana, Looker, Tableau) to build executive-grade dashboards. • Strategic Acumen: Proven ability to create structure in highly ambiguous environments and build target-setting frameworks from scratch. • MarTech Ecosystem: Deep familiarity with connectivity between Salesforce, marketing automation, and product-led data streams. • Executive presence with experience presenting to executive and board audiences, including sound judgment about what data is and isn't ready to share up the chain.