Requirements

• 10+ years in Enterprise B2B marketing analytics, GTM analytics, or growth analytics, with at least 3 years in a people leadership role,
• Experience with complex B2B GTM motions including ABM, enterprise sales cycles, partner-influenced deals, and multi-stakeholder buying journeys,
• Deep expertise in B2B attribution modeling: you understand the fundamental challenges of attributing revenue in long sales cycles with multiple buying group touches, and you have built models that balance rigor with organizational adoption,
• Strong command of how marketing fits into the full revenue engine — you can speak fluently with Sales, Finance, and RevOps about pipeline, coverage ratios, CAC, LTV, and go-to-market efficiency,
• Proven ability to influence strategy: you don't just report what happened, you shape what happens next. You've used data to shift budget (such as Events, Paid Media, etc), change channel mix, or redirect a program — and you can point to the outcome,
• Proficiency with the core marketing and revenue tech stack: Salesforce, Marketo (or HubSpot), BI tools (Tableau, Looker, or equivalent), data warehousing (Snowflake, BigQuery, or similar), and familiarity with ABM/GTM software (Demandbase, 6Sense, etc),
• Strong proficiency in SQL and experience working directly with warehouse data to validate models, investigate anomalies, and support ad hoc analysis,
• Comfortable with statistical modeling, regression analysis, and cohort analysis — you know when to use a model and when a well-structured spreadsheet is more persuasive,
• Strong communicator who can translate analytical complexity into executive-level narratives without losing nuance,
• Experience in fintech, payments, embedded finance, SaaS, or financial services strongly preferred,
• Familiarity with AI/ML applications in marketing analytics — predictive lead scoring, churn modeling, anomaly detection — and a point of view on where these create real leverage vs. hype,
• Comfortable operating in ambiguity, building programs from scratch, and operating without a fully defined playbook

What the job involves

• Marqeta is seeking a Director of Marketing Analytics to serve as the intelligence backbone of our go-to-market engine. This is a senior leadership role for someone who doesn't just measure marketing — they shape it. You will define how Marqeta understands marketing's contribution to revenue, build the analytical infrastructure and team to prove it, and partner across Marketing, Sales, Finance, and Revenue Operations to influence how we invest, prioritize, and grow,
• You will own the full analytics remit for marketing: multi-touch attribution across a complex, Enterprise B2B buying journey, pipeline contribution and influenced revenue modeling, channel performance, campaign effectiveness, and executive-level reporting. Critically, you understand that attribution in B2B is a strategic narrative as much as a technical one. You know how to build models that earn trust from Sales leadership and the CFO, not just satisfy marketing curiosity,
• Define and own Marqeta's B2B marketing attribution strategy and partner with RevOps and Finance to land a measurement framework that Sales and the C-suite trust and use,
• Build the connective tissue between marketing programs, media investments and revenue outcomes: pipeline sourced, pipeline influenced, deal velocity, win rate by segment, and CAC by channel,
• Lead a team of marketing analysts, establishing operating rhythms, analytic standards, and career development frameworks,
• Serve as a senior strategic voice in GTM planning, bringing data-driven POVs to budget allocation, channel strategy, ICP prioritization, and campaign investment decisions,
• Partner with Demand Generation, Product Marketing, and Brand teams to design measurement frameworks and testing protocols,
• Own executive-level marketing reporting to the CMO, CFO, and Board: translate complex data into clear narratives about where marketing is creating enterprise value,
• Build and maintain the marketing data infrastructure in partnership with Data Engineering, ensuring clean, unified data across Salesforce, Marketo, paid channels, and intent platforms,
• Develop forecasting models that project Enterprise NAL pipeline contribution from marketing investments, informing quarterly planning and headcount decisions,
• Lead the marketing org's AI and automation strategy for analytics, identifying where machine learning, predictive scoring, and AI-generated insights can accelerate speed-to-insight,
• Establish a culture of experimentation by designing statistically valid tests across channels and campaigns, and building institutional knowledge from results