Photon

Data Product Manager - Merchandising | Onsite

  • Hybrid
  • full time
  • $60k–$210k/year
  • Posted today

Free account required to apply. No card, and you keep 5 new roles a day for free.

About the role

Key accountabilities / essential functions · Defines the vision and roadmap for merchandising data products and connects each investment to a stated merchandising or enterprise objective. · Runs discovery directly with merchants, category teams, pricing, planning, digital merchandising and adjacent users to understand decisions, workflows, pain points and unmet needs. · Owns prioritization across competing needs such as assortment, category performance, pricing, promotions, supplier performance, item hierarchy, product content and digital merchandising. · Defines business rules, canonical concepts, product requirements, acceptance criteria, KPIs and quality expectations clearly enough for data and engineering teams to build and validate. · Partners with data governance and domain experts to establish trusted definitions, ownership, quality thresholds, lineage and appropriate access for merchandising data. · Uses Databricks and the enterprise data platform to develop scalable, reusable data products rather than one-off reports or disconnected data extracts. · Plans launch and adoption beyond technical release, including workflow integration, training, support readiness, communications and product measurement. · Evaluates opportunities for forecasting, optimization, recommendations, experimentation and AI-enabled merchant decision support. · Maintains a healthy backlog, exposes dependencies early and drives delivery at a predictable rate while adjusting priorities when evidence or strategy changes. Scope, impact and decision making Owns a portfolio of merchandising data products used across business and technology functions. Makes roadmap, scope and sequencing decisions within the product area and recommends investment trade-offs where shared data, platform capacity or business priorities conflict. Impact is measured through adoption, data quality, time to insight and movement in the merchandising outcomes each product is designed to support. Problem solving and complexity Merchandising decisions combine incomplete evidence, seasonal or promotional effects, complex hierarchies and competing commercial objectives. The role must distinguish reusable domain capabilities from local reporting requests, resolve inconsistent definitions and choose what to build when several stakeholders have legitimate claims on the same capacity. Leadership and influence Leads through product vision, evidence, facilitation and influence rather than direct authority. Creates clarity across business, data, engineering, analytics, architecture, security and change-management partners; makes trade-offs visible; and holds the product team accountable for outcomes and adoption. Key relationships and communication · Merchandising and category teams: discovery, product direction, KPI definition, prioritization and adoption. · Pricing, promotions, planning, finance and digital teams: shared measures, decision workflows, trade-offs and cross-domain dependencies. · Data engineering, analytics, data science and architecture: product requirements, feasibility, data models, quality, lineage and delivery sequencing. · Information security, privacy and governance: access, retention, control and responsible AI requirements. Knowledge, skills and experience Required qualifications · 5+ years of relevant product management, data product, analytics product or comparable experience. · Bachelor's degree in a related field, or equivalent practical experience. · Experience owning product vision, discovery, roadmap, prioritization, requirements, launch readiness, adoption and outcome measurement. · Hands-on working knowledge of Databricks and modern lakehouse concepts, including governed data products, pipelines, semantic layers, data quality, lineage and self-service consumption. · Ability to partner effectively with data engineering, analytics, data science, architecture, security, privacy and business teams. · Ability to define product outcomes and KPIs, use evidence to make prioritization decisions and communicate complex data topics in business language. · Working knowledge of agile product delivery, backlog management, dependency planning and change adoption. · Working knowledge of retail merchandising language and economics, including assortment, category management, pricing, promotions, item hierarchy, product lifecycle, supplier performance and margin. Ways of working · Keeping member and business value the deciding factor when scope pressure would cut it first. · Building consensus across functions that have no reporting line to each other. · Changing direction when evidence shows an approach is not working rather than continuing because of sunk cost. · Holding commitments across concurrent workstreams and communicating early when constraints require a trade-off. · Holding data products to ethical, privacy, security, quality and governance standards under pressure to ship. Preferred qualifications · Retail, wholesale club, grocery or consumer commerce experience. · Experience with merchandising analytics, demand forecasting, product information, pricing or promotion optimization. · Experience introducing AI/ML capabilities into merchant workflows and measuring adoption and value. Location type ☒ CSC/Remote ☐ Club ☐ Distribution Center ☐ Perishable DC ☐ Perishable HO ☐ Transportation ☐ Contractor Off Site Working conditions and physical requirements Work is primarily performed in a standard office or remote environment using computers and collaboration tools. The role may require periodic time in clubs, distribution centers or other BJ’s facilities to conduct discovery and understand operational workflows. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work travel requirements Occasional business travel may be required based on product discovery, planning, implementation and stakeholder needs.   Compensation, Benefits and Duration Minimum Compensation: USD 60,000 Maximum Compensation: USD 210,000 Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role. Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees. This position is available for independent contractors No applications will be considered if received more than 120 days after the date of this post

Skills

  • Product management
  • Data product management
  • Databricks
  • Data governance
  • Merchandising analytics
  • Roadmap development
  • Agile methodology
  • Stakeholder management
  • Data modeling
  • KPI definition
  • Demand forecasting
  • Pricing optimization
  • AI/ML integration
  • Business strategy
  • Data quality management
  • Cross-functional leadership

Other PM roles hiring now