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 We are looking for a Director, Marketing Analytics to translate our marketing intelligence strategy into operational excellence and commercial impact. You will lead a multidisciplinary analytics team across data engineering, analytics engineering, visualization, and data science workflows. Sitting at the intersection of marketing strategy, revenue operations, and data engineering, you will serve as a trusted partner to Sales, RevOps, Finance, Product-Led Growth (PLG), and Enterprise Data. You will build our marketing intelligence system. This will focus on three key areas. First, you will optimize how we allocate capital. You will use solid ROI and incrementality frameworks for this. Second, you will identify growth insights by finding predictive buyer and expansion signals. Finally, you will promote data clarity. This involves ensuring we have a well-governed, transparent single source of truth. Grounded in open, explainable attribution models, you will streamline organization-wide decision-making and help fuel long-term growth across the entire customer lifecycle. What You Will Be Doing • 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 . • 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. • 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. • 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. • 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 • 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. • 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). • Data Governance & Taxonomy Expertise: Demonstrated success designing information architectures, metric dictionaries, and governance standards that support automation and AI tools. • Technical Stack Literacy: Hands-on technical comfort with SQL, modern data platforms (BigQuery, dbt), enterprise BI platforms (Tableau), and CRM/MarTech ecosystems (Salesforce, Marketo). • Executive Storytelling & Cross-Functional Orchestration: Exceptional ability to translate complex quantitative models into clear economic narratives and strategic recommendations for executive leadership . • 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 • Hands-on experience operationalizing predictive machine learning models (e.g., lead scoring, propensity models, churn risk) directly into Salesforce for seller actioning. • Experience building measurement frameworks for partner-sourced, partner-influenced, or hyperscaler marketplace revenue. • Direct experience analyzing Product-Led Growth (PLG), consumption-based, or usage-driven SaaS revenue models. #LI-JM5 Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $160,300 $25