Sr. Product Marketing Manager
Job description
About the role
This role translates Smartsheet's global AI narrative into regionally activated guidance for EMEA field teams.
Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.
Key facts
Requirements
8+ years of experience in product marketing, solutions marketing, or GTM strategy in a B2B SaaS environment, with meaningful time spent in or supporting EMEA markets.
Direct experience translating global product narratives into regionally activated field content and sales enablement for European enterprise audiences.
Working knowledge of AI and automation concepts sufficient to engage credibly with technical buyers, solution engineers, and product teams.
Familiarity with the European regulatory and data sovereignty landscape as it relates to enterprise AI adoption (GDPR, AI Act, data residency considerations).
Strong writing and messaging skills to turn complex AI product capabilities into clear, buyer-resonant value claims for a European context.
Comfort working directly with Sales, Customer Success, and field teams across multiple EMEA sub-regions to validate, iterate, and activate positioning in real time.
Proactive and self-directed, with the ability to bring structure to complex, fast-moving environments while juggling multiple high-stakes relationships.
Experience with competitive intelligence and the ability to maintain current, actionable competitive views in a fast-moving market.
Bachelor's degree or equivalent experience required.
Fluency in English is required.
Ability to work in the UK on an ongoing basis.
Nice to have
- EMEA field marketing or sales enablement background.
- Experience with AI product positioning and enablement.
- Experience with the Model Context Protocol (MCP).
Practical notes
You will report to the VP, AI Market Strategy. Typical interview steps
Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.
Good to know
Roles in this area use tools such as Highspot for enablement, Gong for conversation analytics, and content collaboration platforms. Professionals in this field translate global narratives into regionally relevant content while navigating complex compliance landscapes. This role works across product, sales, and customer success teams in a fast-paced growth mode.
Career growth
Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.
About the company
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