Senior Product Manager, Data Products

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.

• 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 outcomes, such as merchandising conversion, receiving efficiency, or analytic integrity.

•  7+ years of progressive experience in product management, with demonstrated ownership of working with data products and production-grade machine learning systems.
• Experience turning internal data infrastructure into externally-facing products or platform capabilities—not just maintaining pipelines, but defining how data becomes a product and customer experiences.
• Strong technical fluency across data pipelines, ML/NLP systems, and data quality tooling; comfort engaging deeply with data engineering teams on architecture, pipeline design, and quality metrics
• Experience with product catalog, taxonomy, or product information management (PIM) systems, ideally in a multi-sided marketplace or platform context
• Proven ability to manage complex cross-functional dependencies across multiple engineering teams (data engineering, application engineering, external partners, POS, ecommerce) and ship cohesive outcomes.
• B2B software experience with an understanding of how platform products are adopted and configured by business operators—not just end consumers
• Experience leveraging AI/ML technologies (including LLMs) to improve product quality, automate classification, or drive intelligent matching is a strong plus
• Excellent communication skills with the ability to create clarity across technical and non-technical stakeholders, translating data platform capabilities into business value
• Experience designing governance models for shared data assets—resolving conflicts between contributors, managing data provenance, and balancing canonical authority with contributor flexibility
• Comfort owning product identifier systems (SKU hierarchies, parent-child product relationships, cross-jurisdiction variants) as a product problem, not just an engineering one

• Experience in cannabis, regulated industries, or verticals with complex compliance-driven product categorization requirements
• Familiarity with modern data stack tooling (dbt, Dagster, Snowflake, or similar orchestration and transformation tools)
• Background in building or scaling B2B marketplace platforms where product identity and catalog interoperability were central challenges
• Experience with product graph or knowledge graph approaches to structuring product data

We are targeting a salary of $149,000 - $201,000 based on the intended level for this role.

In addition to cash compensation, our total rewards package includes:

• Full medical benefits including dental and vision plans to ensure you always have the best care.
• Equity packages in the form of stock options to all employees.
• Technology (hardware, software, reading materials, etc..) allowance
• Flexible vacation and sick days