Product Manager – Tableau Next

We're seeking a Product Manager / Senior Product Manager for Tableau Next to shape the future of Analytics. In this key role, you'll define the vision and strategy for the product and drive the development of our next generation of Analytics product line. Collaborate with top engineers, designers, and product teams to deliver an innovative, intelligent analytics experience—deeply integrated with Salesforce and Data Cloud.

Responsibilities:

• Develop and drive the vision and roadmap for Tableau Next product.

• Establish what "analysis-ready on day one" means and translate it into product requirements.

• Define and deliver high-quality, production-ready product strategies and roadmaps using modern PM practices, with AI as a core part of your workflow — pushing the boundaries of AI-powered tools to drive smarter prioritization, faster discovery, and better outcomes.

• Design and orchestrate complex product workflows where AI agents integrate seamlessly into cross-functional team operations, driving efficiency and innovation at scale.

• Contribute to building and maintaining shared product context — an explicit repository of product principles, constraints, user insights, and standards that enables AI to generate accurate, reliable, and actionable recommendations.

• Critically evaluate AI-generated outputs (e.g., user research summaries, PRDs, roadmap suggestions) for correctness, quality, alignment with business goals, and user impact.

• Conduct market research, user analysis, and competitive benchmarking to uncover trends and opportunities in data integrations.

• Partner with engineering teams to design and deliver scalable, secure, and high-performance conversational analytics solutions.

• Gather and analyze user feedback on the product and identify areas for improvement.

• Collaborate with customers, internal teams (engineering, sales, marketing, and support), and partners to drive successful product adoption.

• Work across platform constraints (entitlements, governance, semantics, performance, security) to ensure experiences are enterprise-ready and trustworthy.

• Lead cross-cloud collaboration to align dependencies, architecture, and outcomes.

Must Have Qualifications:

• 5-10 years of product management experience, specializing in end-to-end analytics experiences including onboarding/setup and workflows that accelerate the path to analysis-ready, trusted insights.

• Proven ability to define product vision, prioritize features, and manage roadmaps while collaborating with cross-functional teams.

• Strong track record of leading teams, driving alignment, and successfully delivering analytics solutions.

• Expert in understanding user needs and translating them into clear, actionable product requirements.

• Hands-on experience with ETL/ELT processes and data connectivity features across different platforms.

• Strong understanding of AI, APIs, authentication protocols, and data connection standards.

• A demonstrated, genuine AI-first approach to product management — using AI to move faster, build fluency across the product lifecycle, and contribute well beyond traditional PM scope.

• Experience using AI tools in product workflows such as discovery, spec writing, competitive analysis, and stakeholder communication.

• Visionary Communication: A proven ability to transform ambiguity into a documented, high-clarity strategy — leaving meetings with a clear path forward that inspires confidence in both management and the engineering team.

• Owner mentality: you thrive in ambiguity, unblock teams, and drive execution with urgency and accountability.

Nice to Have Qualifications:

• Familiarity with Salesforce platform and Data Cloud fundamentals, including how customers manage users, permissions, and admin setup (profiles/permission sets/roles).

• Experience with the Tableau / CRM Analytics user base (or equivalent BI/analytics products), including common personas, adoption patterns, and admin workflows.

• Understanding of enterprise data governance and security (RBAC/ABAC, auditability, lineage) and how these requirements show up in analytics products.

• Hands-on experience with data ecosystems (Snowflake, Databricks, BigQuery, etc.), including connectivity, performance considerations, and semantic modeling.