Senior Data Product Manager

About the role

The Senior Data Product Manager defines, develops and delivers enterprise data products that enable data-driven decision-making, operational efficiency and measurable business outcomes. The role owns the full product lifecycle, from strategy and roadmap to delivery, adoption and continuous improvement, and requires a strong grasp of modern data platforms, data architecture, data modeling, analytics workflows and data governance.

Key responsibilities

• Strategy and planning (about 50%): turn business goals and user needs into product strategy, communicate priorities to development, matrixed and partner teams, and set goals, metrics and analytics to measure product value
• Manage and groom the product backlog, partner with Finance on business plans for new opportunities, and monitor research and the competitive landscape
• Delivery and execution (about 20%): run user research and testing, document and review quality and change control standards, create and prioritize user stories, and take part in standups, iteration planning, demos and retrospectives
• People (about 30%): foster collaboration with Engineering and UX, advocate for the end user, guide junior team members, and contribute to communities of practice and talent activities
• Maintain comprehensive product documentation, including roadmaps, user stories, requirements, data definitions, acceptance criteria, process flows, data quality expectations, release documentation and product operating models

Required profile

• At least 18 years old and legally permitted to work in the United States
• Preferred: 3-6 years of relevant experience, including as a Product Manager in a modern software development environment
• Bachelor's degree or equivalent in a related field
• Ability to work in a fast-paced environment where priorities shift regularly, and to influence functional and technical colleagues

Required skills

• Modern software product management practices and agile methodologies, including XP principles such as paired programming, test-driven development and continuous deployment
• User research and testing, and the ability to define goals, metrics and analytics
• Creating, prioritizing and accepting user stories
• SQL and data analysis techniques to validate data quality and measure product performance