Staff, Data Product Manager

Responsibilities

• Define and own the vision, strategy, and roadmap for data products (e.g., dashboards, data platforms, model features and enhancements) that support data-driven insights, decisioning, and actions.
• Act as the bridge between data engineers, data scientists, analysts, and business stakeholders to translate business needs into data solutions.
• Develop product requirements and user stories focused on data access, usability, performance, and quality.
• Prioritize data initiatives based on business impact, technical feasibility, and data availability.
• Ensure proper data governance, privacy, and compliance practices are followed.
• Ensure teams have self-service access to GTM data via platforms, tools, and interfaces.
• Monitor and improve data quality, reliability, and user adoption of data tools and features, providing regular reporting on effectiveness and areas for improvement.
• Define and track success metrics for data products, ensuring they meet business and technical goals.
• Foster a culture of data-driven decision making by making data products intuitive and accessible.
• Partner with finance, product, and sales teams to ensure that data products serve the needs of our internal customers.
• Stay informed about industry trends, tools, and best practices in data product management and data enablement.
• Develop training materials to empower teams across the organization to use data effectively for decision-making, campaign execution, and customer engagement.
• Lead initiatives to improve data literacy across teams, ensuring that data is accessible, understandable, and actionable.
• Identify opportunities for innovation in how we leverage data, driving new methodologies and technologies to enhance data utilization and customer experience.

Requirements

• 8 years of experience in product management, engineering, or analytics with a focus on data products, analytics platforms, or data infrastructure, with a preference for direct experience supporting GTM or sales analytics in a SaaS environment.
• Strong understanding of data platforms, data pipelines, and analytics/BI tools (e.g., AWS, Snowflake, DBT, Tableau).
• Proficiency with SQL and familiarity with data modeling concepts.
• Experience working with data teams (engineering, analytics, and data science).
• Knowledge of data governance, privacy regulations, and data security standards.
• Strong communication and collaboration skills, with the ability to work across technical and non-technical stakeholders.
• Experience with agile product development methodologies.
• Strong project management skills, with the ability to prioritize and execute multiple initiatives simultaneously.
• Strong analytical and problem-solving skills with the ability to translate data insights into actionable strategies.

Nice-to-Haves

• Experience with GTM technology stacks (e.g., Salesforce, Gong, etc).
• Experience with AI products such as Claude, Cortex, Glean, Gemini.
• Experience with project management software such as Jira & Airtable.
• Knowledge of data governance and data privacy regulations (e.g., MNPI compliance).
• Advanced degree (MBA, Master’s in Engineering, Analytics, Data Management or related fields) is a plus.