Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — 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 @ 1
Tableau @ 6
Data Science @ 4
Hiring @ 4
Leadership @ 4
API @ 4
BI @ 6
LLM @ 4
Snowflake @ 7
Compliance @ 4
Salesforce @ 3
Claude Code @ 4
AI @ 4
Agentic AI @ 4
Data Pipelines @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — 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 (100% remote) is hiring a Marketing Analytics Director to lead the evolution of the marketing data stack and raise analytical rigor across the marketing organization. This is a builder-practitioner role at the intersection of Data Science, Marketing Strategy, GTM, and AI Operations. The role focuses on building systems (including agentic AI agents) that improve how analysts work, and on driving demand generation across the full marketing funnel.
Responsibilities
- Serve as the primary strategic partner to GTM leadership (VPs of Demand Gen and Regional/Events, Head of Marketing Ops, CMO, Revenue Operations, Sales leadership, and others) to translate complex data into a clear roadmap for demand generation and revenue growth.
- Architect and own a dual-track target-setting and forecasting framework that balances top-of-funnel velocity with deep-funnel quality optimized for Grafana Cloud conversion and retention.
- Develop, maintain, and productionize predictive models (attribution, MMM, LTV) to predict campaign impact and steer budget allocation toward highest-ROI channels.
- Oversee marketing data warehouse architecture (primarily Google BigQuery) to create a scalable single source of truth that connects product usage data with marketing touchpoints.
- Perform causal inference and predictive trend analysis; investigate anomalies and isolate windows of impact for spikes, dips, or campaign performance.
- Translate technical outputs into executive-grade narratives and presentations for the executive team and board.
Utilizing AI and Automation
- Deploy LLM-powered, agentic systems (examples: Claude Code, MCP-based tooling or comparable) to monitor BigQuery datasets and automatically flag funnel-quality shifts before they impact revenue.
- Implement orchestration and automation patterns (N8N, custom MCP servers, or equivalent) to build self-healing data pipelines and automated responses to market signals (e.g., spend shifts based on conversion anomalies).
- Build AI-driven predictive quality scoring models to separate high-value potential users from low-signal volume to help Sales and Marketing prioritize.
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) in a high-growth SaaS or PLG environment.
- Demonstrated history as a force multiplier: built tooling, rituals, evaluator systems, or frameworks that 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 engineering experience building and shipping agentic systems (Claude Code, MCP, or comparable). Strong understanding of LLM failure modes and mitigations; experience building evaluator agents, prompt-grading systems, or analytical quality tooling in production.
- Experience building complex logic and integrations using N8N, custom API orchestration, or MCP-based tooling.
- Advanced proficiency with visualization and BI tools (Grafana, Looker, Tableau) to build executive-grade dashboards.
- Strong strategic acumen: ability to create structure in ambiguous environments and build target-setting frameworks from scratch.
- Familiarity with MarTech connectivity (Salesforce, marketing automation, product-led data streams) and presenting to executive/board audiences.
Benefits & Compensation
- In Canada, OTE compensation range: CAD 180,939 - CAD 217,128. Actual compensation may vary by level, experience, and skillset; roles include Restricted Stock Units (RSUs).
- 100% remote company across 40+ countries; in-person onboarding is provided.
- Global annual leave policy: 30 days per annum (3 days reserved for Grafana Shutdown Days); compliance with local legislation where applicable.
- Transparent, innovation-driven culture, supportive leadership, and clear career growth pathways.
Additional Notes
- Bonus: Bachelor's or Master's in a quantitative field (Data Science, CS, Statistics, Business Analytics) or MBA/MS in Data Science is a plus.
- Grafana Labs may utilize AI tools in the recruitment process to assist with CV matching; recruitment team will manually review inbound CVs.
- The posting targets candidates applying in Canada (role is listed as Canada - Remote); compensation ranges are country specific and recruiters will discuss market-specific pay ranges for other locations.