Technical Product Manager (Marketing Technology), Remote

Role overview Drive product strategy and execution for marketing-technology platforms that power top-of-funnel growth. The role sits at the intersection of business stakeholders, analysts, and engineering teams, translating strategic priorities into scalable, high-quality products and measurable outcomes.

Responsibilities - Lead product discovery, definition, and delivery for platforms supporting the marketing engine, from problem framing through rollout. - Partner with business owners and end users to uncover needs, frame opportunities, and convert them into product requirements, user stories, and clear success criteria. - Cultivate a shared vision across stakeholders for the problem space, constraints, and ideal end state, and advocate for that perspective. - Continuously optimize live workflows by monitoring key metrics, gathering user feedback, and iterating on capabilities. - Author detailed user stories capturing business rationale, requirements, and measurable outcomes. - Develop short- and long-term roadmaps that balance value and risk, with built-in room for iteration.

Requirements - 5+ years of product management experience in marketing technology, technology-enabled services, or SaaS products. - Demonstrated use of data and primary research to inform solution design and build stakeholder understanding. - Solid grasp of the software development lifecycle, preferably with Agile or Scrum team experience. - Product development experience within a healthcare-technology context.

Nice to have - Deep martech domain expertise across platforms such as CDPs, DAMs, CMS, and marketing automation, and how unified data enables personalization and agentic marketing. - Hands-on experience with tools like Hubspot, Salesforce, Seismic, Gong, ZoomInfo, or Chili Piper. - Familiarity with Salesforce CRM capabilities, customer data platforms, identity resolution, consent and preference management, and working SQL knowledge. - Track record of identifying and deploying AI-driven use cases that improve pipeline and efficiency.