Director, Marketing Analytics

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

What You Will Be Doing

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  Capital Allocation & Attribution: Operationalize open, explainable multi-touch attribution (MTA) and ROI frameworks that measure full-funnel contribution and ensure global budgets are allocated efficiently.
  
  


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  Customer Journeys & Predictive Signals: Build customer journey frameworks in partnership with Marketing Ops to model the "moments that matter", while overseeing the deployment of predictive buyer intent and expansion signals to growth and sales teams.
  
  


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  Information Architecture & AI Readiness: Standardize data taxonomy, metric definitions, and semantic models (dbt/BigQuery) across our marketing ecosystem, ensuring our data foundations are structured, clean, and optimized for AI data interfaces.
  
  


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  Cross-Functional Alignment & Visualizations: Partner across Sales, RevOps, Finance, and PLG to align on shared metrics, delivering executive-ready visualizations (Tableau) and data-backed stories that simplify planning, execution, and course correction.
  
  


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  Team Leadership & Capacity Governance: Guide, mentor, and orchestrate a multidisciplinary analytics team, establishing clear intake triage processes that shield team capacity for high-impact strategic milestones.
  
  

What You Bring

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  10+ years of leadership experience managing multidisciplinary analytics teams, with a track record of unifying data engineers, analytics engineers, data scientists, and BI analysts toward shared commercial goals.
  
  


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  Proven Measurement & Financial Acumen: Deep expertise in marketing measurement, modern attribution models, incrementality testing, customer journey mapping, and SaaS unit economics (CAC, LTV, NRR, Payback).
  
  


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  Data Governance & Taxonomy Expertise: Demonstrated success designing information architectures, metric dictionaries, and governance standards that support automation and AI tools.
  
  


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  Technical Stack Literacy: Hands-on technical comfort with SQL, modern data platforms (BigQuery, dbt), enterprise BI platforms (Tableau), and CRM/MarTech ecosystems (Salesforce, Marketo).
  
  


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  Executive Storytelling & Cross-Functional Orchestration: Exceptional ability to translate complex quantitative models into clear economic narratives and strategic recommendations for executive leadership.
  
  


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  Education: Bachelor’s degree in a quantitative or business field (such as Statistics, Economics, Data Science, or Business Administration) or equivalent professional experience.
  
  

Bonus Points

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  Hands-on experience operationalizing predictive machine learning models (e.g., lead scoring, propensity models, churn risk) directly into Salesforce for seller actioning.
  
  


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  Experience building measurement frameworks for partner-sourced, partner-influenced, or hyperscaler marketplace revenue.
  
  


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  Direct experience analyzing Product-Led Growth (PLG), consumption-based, or usage-driven SaaS revenue models.
  
  

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