Senior Product Manager - Data Platform & Analytics

• Own the product strategy, roadmap, and delivery of foundational data platform capabilities supporting Analytics, Reporting, and AI/ML solutions.
• Define requirements for backend data structures, data models, pipelines, and data services to enable scalable, consistent, and performant analytics.
• Partner closely with Engineering, Data Science, Analytics, and Product teams to translate business needs into well-defined data product requirements.
• Drive data standardization, quality, governance, accessibility, and reusability across product lines.
• Define clear success metrics for data reliability, performance, scalability, cost efficiency, and business value.
• Balance long-term platform investments with immediate product and customer needs, managing priorities and technical dependencies.

• 5-8+ years of Product Management experience, with significant exposure to data platforms, analytics, or enterprise data products.
• Strong technical understanding of data architecture, data modeling, ETL/ELT pipelines, data warehouses, lakehouses, APIs, and cloud data infrastructure.
• Experience defining data products that support business intelligence, advanced analytics, and AI/ML applications.
• Familiarity with cloud platforms such as GCP and modern data technologies.
• Ability to collaborate effectively with Data Engineering and Architecture teams, understanding technical trade-offs without necessarily being a hands-on engineer.
• Strong product discovery, requirements definition, roadmap prioritization, stakeholder management, and agile execution skills.
• Retail, pricing, promotions, or merchandising data domain experience is highly desirable.
• Ability to thrive in fast-paced, ambiguous environments, demonstrating ownership, adaptability, strong problem-solving skills, and a bias for action.

Ideal Candidate

A technically fluent, outcome-driven Product Manager who understands how to turn complex backend data infrastructure into scalable, reusable data products. Someone who can bridge business, analytics, and engineering needs, establish strong data foundations, and accelerate the delivery of customer-facing analytics and intelligence capabilities.