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Head of Marketing Operations

Fireworks AI · United States

RemoteImported listingfull-time3 days ago

About The Role

Join Fireworks as the Head of Marketing Operations, where you will build the infrastructure for scalable marketing and manage the day-to-day operations of the team. You will own the marketing tech stack, data model, lifecycle, and analytics, ensuring marketing becomes a predictable pipeline engine. Additionally, you will oversee planning rhythms, budget, prioritization, and program management, keeping the marketing team aligned and on track. Success will be measured by program delivery, budget accuracy, and team velocity.

  • Responsable de la gestion de l'ensemble de la pile technologique marketing, y compris la sélection, l'implémentation, l'intégration et les normes qui régissent le flux de données entre les systèmes.
  • Diriger le rythme opérationnel de l'équipe marketing, y compris le processus de planification annuel et trimestriel, la définition et le suivi des objectifs, les examens d'affaires hebdomadaires.
  • Posséder l'ensemble du cycle de vie, de l'internaute anonyme à la clôture, y compris la notation des leads, les définitions MQL et PQL, l'application des SLA et le passage à l'équipe de vente.
  • Calm under pressure with strong opinions held loosely
  • Deep fluency in HubSpot or Marketo, Salesforce, and at least one BI tool (Looker, Tableau, Sigma)
  • Proven track record at a startup or fast-scaling growth-stage company
  • 8+ years in marketing operations with at least 3 years in a leadership role
  • Comfort owning data quality, GDPR/CCPA compliance, and attribution debates
  • Experience managing budget, vendor relationships, and headcount planning alongside a marketing leader
  • Track record running planning cadences, OKRs, and cross-functional program management for a marketing org
  • Experience building marketing operations from scratch or replatforming at a B2B SaaS company
  • Past experience at a developer-first or product-led growth company
  • SQL fluency
  • Experience with hybrid PQL and MQL scoring models

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