Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 ā basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 ā daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 ā you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 ā exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Marketing @ 4
Grafana @ 4
Python @ 4
SQL @ 4
Looker @ 6
Statistics @ 4
Tableau @ 6
Machine Learning @ 4
Data Science @ 4
Hiring @ 4
Leadership @ 4
API @ 4
BI @ 4
LLM @ 4
Snowflake @ 7
Salesforce @ 3
Claude Code @ 4
Observability @ 4
AI @ 4
Agentic AI @ 4
Data Pipelines @ 4
- 1-2 ā basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 ā daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 ā you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 ā exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Grafana Labs is hiring a Marketing Analytics Director to lead the evolution of the marketing data stack and raise analytical rigor across the marketing organization. This role sits at the intersection of Data Science, Marketing Strategy, GTM, and AI Operations and focuses on building systems (including agentic AI) that enable better forecasting, predictive modeling, and automated responses to market signals. The role emphasizes architecting a unified source of truth in Google BigQuery, designing predictive models, and implementing BI frameworks to drive demand generation and long-term retention.
Responsibilities
- Serve as the primary strategic partner to GTM leadership (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.
- Architect and own a sophisticated dual-track forecasting/target-setting framework that balances top-of-funnel volume with high-intent lead quality, optimized for Grafana Cloud conversion and retention.
- Develop and maintain machine learning models (Attribution, Marketing Mix Modeling (MMM), LTV) to predict campaign impact and steer budget allocation to highest-ROI channels.
- Oversee marketing data warehouse architecture in Google BigQuery to ensure a scalable single source of truth connecting product usage data with marketing touchpoints.
- Perform causal inference and predictive trend analysis to investigate anomalies (spikes, regional dips, overperforming campaigns) and isolate causal windows.
- Transform technical outputs into concise executive narratives; present to executives and board audiences and provide deeper analysis when requested.
Utilizing AI and Automation
- Deploy LLM-powered agents (e.g., Claude Code, MCP-based tooling, or comparable) to monitor BigQuery datasets and automatically flag quality shifts in the funnel.
- Implement orchestration patterns (N8N, custom MCP servers, or equivalent) to build self-healing data pipelines and automated responses to market signals (for example, automated spend shifts based on conversion anomalies).
- Build and deploy AI-driven scoring models that separate high-value potential users from low-signal volume to help Sales and Marketing prioritize effectively.
Requirements
- 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) within a high-growth SaaS or PLG environment.
- Demonstrated history of building tooling, rituals, evaluator systems, or frameworks that materially improved other analysts or the broader org.
- 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 just a user); experience building and shipping agentic systems with Claude Code, MCP, or comparable tools; familiarity with evaluator agents and prompt-grading systems.
- Hands-on experience building complex logic and integrations using N8N, custom API orchestration, or MCP-based tooling.
- Advanced proficiency with modern visualization/BI tools (Grafana, Looker, Tableau) to build executive-grade dashboards.
- Familiarity with connectivity across Salesforce, marketing automation, and product-led data streams.
- Strong strategic acumen and executive presence; experience presenting to executive and board audiences and making judgment calls about data readiness.
Bonus
- Bachelor's or Master's degree in a quantitative field (Data Science, Computer Science, Statistics, Business Analytics). MBA or MS in Data Science is a significant plus.
Compensation & Other Details
- In the United States, the OTE compensation range for this role is $178,503 - $214,203. Actual compensation may vary based on level, experience, and skillset. All roles include Restricted Stock Units (RSUs).
- Grafana Labs is a 100% remote company. The company offers in-person onboarding, a global annual leave policy of 30 days per annum (with 3 days reserved for Grafana Shutdown Days), and a remote-first global culture.
Company & Culture
- Grafana Labs builds open observability cloud products (Grafana Cloud) and emphasizes open source, open standards, and an innovation-driven remote culture. The company has 1,600+ team members across 40+ countries and customers including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce.