Lead Product Marketing Manager (Enterprise)

TL;DR

Lead Product Marketing Manager (Enterprise): Developing and executing GTM strategies for the mid and large enterprise segment with an accent on sales plays and competitive positioning. Focus on driving pipeline and revenue through integrated marketing campaigns and translating product vision into compelling enterprise narratives.

Location: Must be based in the United States

Company

SaaS platform empowering ecommerce brands to leverage first-party data for personalized experiences.

What you will do

• Define and prioritize field selling motions for mid and large enterprise segments, synthesizing market trends and competitive dynamics.
• Design end-to-end Enterprise sales plays, from ICP definition through field launch and enablement.
• Lead integrated marketing campaigns, owning strategic concepts and anchor assets like maturity assessments and industry benchmarks.
• Maintain and evolve core enterprise assets, including pitch decks, landing pages, and discovery frameworks.
• Translate product vision and roadmap into narratives for enterprise audiences and influence roadmap prioritization.
• Track GTM performance across pipeline and closed-won rates to provide structured recommendations for optimization.

Requirements

• 8+ years of product marketing experience, with a significant focus on B2B SaaS.
• Direct experience marketing to mid-market and enterprise buyers is required.
• Proven ability to own GTM programs independently from positioning through execution and performance readout.
• Experience supporting complex, multi-stakeholder sales cycles and enabling large sales organizations.
• High craft bar for written and visual work suitable for executive and external audiences.
• Ability to drive alignment across teams with competing priorities through influence.

Culture & Benefits

• Comprehensive health, welfare, and wellbeing benefits.
• Participation in the company’s annual cash bonus plan and equity.
• Culture that values unique backgrounds and diverse perspectives.
• Focus on AI fluency and the responsible use of AI tools in the workplace.
• Flexible approach to candidates who are close but not exact matches for the role.