The Opportunity We are seeking a
Marketing Analytics Director to lead the evolution of our marketing data stack and raise the analytical rigor of the entire marketing organization. This is a critical role for a builder-practitioner who works at the intersection of Data Science, Marketing Strategy, GTM, and AI Operations. You won't just report on the funnel. You will build the systems that make every analyst on this team sharper, including the AI agents themselves.
As the
Marketing Analytics Director , you will be the lead architect of our data-driven growth engine, connecting high-level strategy with advanced technical execution. You will move beyond traditional reporting to build a self-sustaining marketing ecosystem, leveraging Google BigQuery, Grafana, and agentic AI to create a unified source of truth and a culture of analytical rigor. Your mandate is to move the needle on demand generation across the entire marketing funnel, while raising the standard for how analytical work gets produced, challenged, and shipped across the org.
You will architect a dual-track target-setting framework that balances high-velocity top-of-funnel growth with deep-funnel quality, ensuring GTM resources are directed toward high-converting user cohorts optimized for Grafana adoption and long-term retention.
You will be expected to engineer the underlying data schemas, design predictive models, and implement the BI frameworks that shape our global GTM strategy. We are looking for a technical expert who can translate complex data into clear executive-level direction and who proactively builds systems that prevent AI-generated noise from drowning out actual signals.
What You'll Be Doing- 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.
Bonus Points For- Education: Bachelor's or Master's degree in a quantitative field (Data Science, CS, Statistics, Business Analytics). MBA or MS in Data Science is a significant plus.
In the US, the OTE compensation range for this role is $178,503 - $214,203. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes-RSUs help us stay aligned and invested as we scale globally.
*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market's defined pay range & benefits at the beginning of the process.
