Data Product Manager, Sales (Director)

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About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

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Data Product Manager, Sales (Director)

Office hybrid in San Francisco, CA

The Data Solutions team powers Salesforce's digital transformation by harnessing data and AI to drive strategic and automated decisions across the organization.As Sales Data Science within Data Solutions, we're dedicated to accelerating revenue growth and elevating customer success. Leveraging Salesforce technology, we build reliable data and AI products that empower sellers to discover their next deals while delivering powerful insights that enable leaders to set strategic priorities. Data is the fuel for both humans and agents—and we own the entire supply chain. From creation and storage through transformation to deployment in dashboards, algorithms, data products, insights, and experiments, we maintain a trust-first approach that ensures responsible data practices at every step.

The Opportunity:

We are seeking an experienced and visionary Data Product Manager to lead the evolution of data products within our Sales domain, operating in a data mesh architecture. In this pivotal role, you'll bridge sales business needs with advanced data solutions, creating data products that empower our sales teams with actionable insights and accelerate revenue growth. You'll champion the "data as a product" philosophy, ensuring our sales stakeholders have data that is discoverable, addressable, trustworthy, and interoperable.

The Role: 

As a Director in Data Product Management on the Sales Data Science team, you'll lead the development and productionalization for sales data use cases. You'll play a pivotal role in working with cross functional stakeholder and engineering teams to build dependable data products for real-time dashboards, predictive solutions and agentic applications. You will be deeply involved and driving data platform capabilities which ensure trusted data products, with high quality, governance, lineage, and reliability. Your work will enable the creation of powerful data mesh products which will serve an enterprise audience. Throughout, you'll ensure compliance with Product Legal, Data Governance, and Privacy/Consent standards. Your efforts will drive seamless data integration, activation, and broad organizational adoption.

What You'll Do:

• Data Product Strategy & Roadmap: Define and execute the vision, strategy, and roadmap for data products in the Sales domain, aligning with overall business objectives and data mesh principles.

• Data-Driven Mindset: You're a data PM at heart, living by the principle "What is not measured cannot be improved" by expertly defining, measuring, and monitoring adoption metrics and business impact metrics.

• Stakeholder Collaboration: Partner closely with Sales leadership, operations, and individual contributors to deeply understand their challenges, data needs, and opportunities for data-driven improvement.

• Requirements Gathering & Prioritization: Translate complex business requirements into clear, concise, and actionable data product specifications and user stories, prioritizing features based on business value and technical feasibility.

• Data Product Ownership: Act as the product owner for sales data products, managing the entire product lifecycle from ideation to launch and continuous iteration. This includes defining success metrics, monitoring performance, and gathering feedback for enhancements.

• Data Mesh Evangelist: Champion data mesh principles within the Sales domain, advocating for data ownership, domain-oriented data products, self-serve capabilities, and federated computational governance.

• Technical Acumen: Work closely with data engineers, analytic engineers, and data scientists. You'll understand the technical complexities of data p