Senior Product Manager, Data Products - Dutchie

About Dutchie

Founded in 2017, Dutchie is a comprehensive technology platform powering dispensary operations, while providing consumers with safe and easy access to cannabis. Dutchie aims to further support the positive societal change the cannabis industry brings to the world through wellness benefits, social justice, and empowering local communities through tax revenue. Powering thousands of dispensaries across 40+ markets throughout the United States and Canada, Dutchie is the leading technology company in the cannabis space and was named in Fast Company’s 10 Most Innovative Companies in North America and listed two years in a row on LinkedIn’s Top 50 Startups.

Dutchie has raised over $600M in funding to date, backed by D1 Capital Partners, Tiger Global, Dragoneer, DFJ Growth, Thrive Capital, Howard Schultz, Snoop Dogg’s Casa Verde Capital, Gron Ventures, members of the founding team at DoorDash, Kevin Durant’s Thirty Five Ventures, and other notable angel investors.

About This Job

As the Senior Product Manager for Data Products, you will own the vision, strategy, and roadmap for key platform products that leverage Dutchie ’s massive data assets to solve high-impact business problems. You will focus on critical data domains, ranging from product identity and taxonomy to advanced AI-driven systems. This includes:

• Developing and governing the core Product Catalog and data platform.
• Enhancing recommendations systems for e-commerce.
• Optimizing Ads optimization systems.
• Pioneering new data-intensive initiatives that are foundational to the Dutchie platform.

This is a high-impact, deeply cross-functional role. Your products will serve internal teams and external customers, ensuring that a clean, consistent data layer compounds value across all surfaces, workflows, and analytics that span retailers.

What You'll Do...

• Own the end-to-end product vision, strategy, and roadmap for a portfolio of data products consumed across ecommerce, POS, B2B, and analytics.
• Partner closely with Data Engineering to evolve the underlying data platform—including matching, classification, canonical naming, and quality—to deliver measurable customer and business outcomes.
• Define and ship data-driven experiences for our customer bases: retailer-facing (e.g., operational efficiency), business-facing (e.g., content contribution via partner portals), and internal (e.g., APIs, SLAs).
• Develop next-generation AI and Machine Learning systems, such as next best action and recommendations engines, to drive significant product improvements.
• Own the architecture and governance models for critical data assets (e.g., product identifiers, taxonomies), resolving conflicts and balancing canonical authority with contributor flexibility.
• Translate data coverage, quality, and structure into measurable business out