Product Data Manager- Supply Chain

Photon; Boston (MA); On-site; USD 120,000 - 170,000; Full time

Job summary

Photon is seeking a Data Product Manager for Supply Chain to own the vision, roadmap, and prioritized requirements for trusted data capabilities across inventory, replenishment, distribution, and fulfillment. You will interface with engineering, analytics, and business teams to deliver governed Databricks-based data products that drive tangible operational value.

The role focuses on turning descriptive visibility into predictive and prescriptive decision support, while planning launches,

Qualifications

• 5+ years of relevant product management or data product experience.
• Bachelor's degree in 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 supply chain language and strategy, including inventory, replenishment, forecasting, purchase orders, distribution-center operations, transportation, fulfillment, service levels and exception management.

Responsibilities

• Defines and maintains the roadmap for supply chain data products, aligning investments to service, inventory, productivity, cost and member-availability objectives.
• Runs discovery with supply chain operators and leaders in clubs, distribution centers, transportation, replenishment, fulfillment and planning to understand decisions and operational constraints.
• Owns prioritization across inventory visibility, in-stock and out-of-stock insights, replenishment, DC throughput, transportation, order visibility, exception management and network performance.
• Defines canonical business concepts, operational KPIs, business rules, event requirements, latency expectations, acceptance criteria and data quality thresholds.
• Partners with engineering, analytics and architecture to deliver governed products on Databricks that support both analytical and operational workflows.
• Builds a path from descriptive visibility to predictive and prescriptive decision support, including exception alerts, demand sensing, inventory optimization and scenario planning where justified by evidence.
• Plans launch, workflow integration, training, support readiness and adoption with operational users, recognizing that value is realized only when decisions and behaviors change.
• Makes dependencies across merchandising, clubs, finance, vendors, logistics systems and shared data visible before they affect committed outcomes.
• Measures product performance through adoption, timeliness, quality, decision-cycle improvement and the operational outcome each product is intended to influence.

Skills

Product management

Data product

Analytics product

Stakeholder collaboration

Agile delivery

Supply chain language

Education

Bachelor's degree

Tools

Databricks

Job description

For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. Our current focus and innovation in Digital Hyper expansion TM offers nearly limitless opportunities for career growth. For a brief 1-minute video about us, you can check out https://youtu.be/uJWBWQZEA6o.

Photon is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We bring out the best in each other.

We are looking for a Product manager who has extensive exp in Data Product And Supply chain.

Job Title: Data Product Manager- Supply chain

Education: Bachelor's in computer science

Job purpose

Data Product Managers decide what gets built and why for supply chain data products. This role owns the vision, roadmap, prioritization and requirements for trusted data capabilities supporting inventory flow, replenishment, distribution, transportation, fulfilment and operational decision-making. It connects supply chain strategy to reusable products on the Databricks enterprise data platform and is accountable for adoption, data trust, operational value and time to action.

Key accountabilities / essential functions

• Defines and maintains the roadmap for supply chain data products, aligning investments to service, inventory, productivity, cost and member-availability objectives.
• Runs discovery with supply chain operators and leaders in clubs, distribution centers, transportation, replenishment, fulfillment and planning to understand decisions and operational constraints.
• Owns prioritization across inventory visibility, in-stock and out-of-stock insights, replenishment, DC throughput, transportation, order visibility, exception management and network performance.
• Defines canonical business concepts, operational KPIs, business rules, event requirements, latency expectations, acceptance criteria and data quality thresholds.
• Partners with engineering, analytics and architecture to deliver governed products on Databricks that support both analytical and operational workflows.
• Builds a path from descriptive visibility to predictive and prescriptive decision support, including exception alerts, demand sensing, inventory optimization and scenario planning where justified by evidence.
• Plans launch, workflow integration, training, support readiness and adoption with operational users, recognizing that value is realized only when decisions and behaviors change.
• Makes dependencies across merchandising, clubs, finance, vendors, logistics systems and shared data visible before they affect committed outcomes.
• Measures product performance through adoption, timeliness, quality, decision-cycle improvement and the operational outcome each product is intended to influence.

Scope, impact and decision making

Owns an end-to-end portfolio of supply chain data products and makes roadmap, scope and sequencing decisions within that portfolio. Recommends trade-offs across operational domains and shared platform capacity. Products may serve corporate, distribution-center, club and field users, with impact measured through adoption, data quality, decision speed and relevant supply chain outcomes.

Problem solving and complexity

Supply chain problems are cross-functional, time-sensitive and dependent on rapidly changing inventory, order and logistics signals. The role must reconcile definitions across systems, balance real-time needs against feasibility and distinguish root causes from symptoms while designing products that work in operational settings.

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

• Supply chain, logistics, replenishment, fulfillment and distribution leaders: strategy, discovery, KPI definition, prioritization and adoption.
• Club operations and merchandising: inventory availability, workflow needs and cross-domain decisions.
• Data engineering, analytics, data science, architecture and platform teams: data models, event patterns, performance, quality and delivery.
• Technology application teams and external partners: source-system dependencies, integration requirements and operational readiness.

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 supply chain language and strategy, including inventory, replenishment, forecasting, purchase orders, distribution-center operations, transportation, fulfillment, service levels and exception management.

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, distribution, logistics or omnichannel fulfillment experience.
• Experience with WMS, TMS, ERP, order management, inventory, robotics or automation data.
• Experience with control towers, forecasting, optimization, event-driven data products or operational AI.