Principal Data Product Manager
New
J
JobgetherProduct Management
United StatesFull-TimePrincipal
SalaryCompetitive annual salary range of $200,000 – $250,000 USD
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Job Details
- Experience
- 10+ years
- Required Skills
- Software DevelopmentArtificial IntelligenceMachine LearningProduct ManagementData engineeringRESTful APIsData analytics
Requirements
- 10+ years of experience in Product Management, with significant experience building data, analytics, platform, or AI-powered products.
- Proven track record defining, launching, and scaling products driven by data, machine learning, analytics, or recommendations.
- Deep understanding of data collection, modeling, governance, measurement, and exposure within products and platforms.
- Strong knowledge of data engineering, analytics, machine learning, and software development concepts.
- Ability to translate complex technical capabilities into simple, valuable customer experiences.
- Experience creating product strategies where data is a key competitive advantage.
- Strong systems-thinking approach with the ability to identify reusable capabilities across products.
- Experience with data products, analytics platforms, recommendation systems, AI-powered experiences, or workflow automation.
- Familiarity with modern data platforms, semantic layers, APIs, governance frameworks, data sharing, and AI/ML ecosystems.
- Excellent communication, stakeholder management, and executive-level influence skills.
Responsibilities
- Define the long-term product vision and strategy for data as a core platform capability.
- Identify opportunities to improve customer experiences, products, and business outcomes through data-driven solutions.
- Build and manage roadmaps across data products, analytics, recommendations, automation, and AI capabilities.
- Establish scalable data capabilities that support multiple products and teams.
- Improve data accessibility, governance, discoverability, and consistency through shared frameworks.
- Enable product teams to leverage trusted data assets.
- Define requirements for AI-enabled products, analytical tools, and workflow automation initiatives.
- Partner with technical and business stakeholders to align priorities, investments, and execution plans.
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