Data Product Manager - Membership | Onsite

Photon•United States,

1d•$60,000 - $210,000•Onsite

About The Position

The Data Product Manager - Membership role is responsible for defining and maintaining the roadmap for membership data products. This role connects product investments to stated growth, engagement, renewal, retention, and member-value objectives. The position involves running discovery sessions with various teams such as Membership, Marketing, CRM, Personalization, Digital Product, Member Care, and Finance to understand their decisions, journeys, and operational needs. The role owns prioritization across key areas including member identity and profile, Member 360, acquisition, onboarding, engagement, lifecycle, renewal, retention, offers, audiences, attribution, and lifetime-value capabilities. The Data Product Manager defines member and household concepts, lifecycle states, business rules, KPIs, identity requirements, quality thresholds, and acceptance criteria in partnership with data governance and domain owners. They will partner with data, engineering, and analytics teams to deliver secure, reusable Databricks data products supporting reporting, activation, experimentation, personalization, and AI use cases. Ensuring privacy, consent, security, and responsible-use requirements are designed into member data products is crucial. The role also evaluates opportunities for predictive capabilities like propensity, churn, next-best-action, segmentation, and recommendations, applying evidence and measurable outcomes before scaling. Planning for launch, activation, stakeholder readiness, communications, training, and adoption measurement across consuming teams and channels is also a key responsibility. Product performance will be measured through adoption, trust, time to activation, and impact on membership outcomes.

Requirements

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 membership and loyalty business language and strategy, including acquisition, onboarding, engagement, tiers, renewal, retention, churn, offers, householding and lifetime value.

Nice To Haves

Retail, wholesale club, subscription, loyalty, financial services or digital commerce experience.
Experience with customer or member data platforms, identity resolution, CRM activation, personalization or marketing measurement.
Experience developing governed predictive or AI capabilities for member lifecycle decisions.

Responsibilities

Defines and maintains the roadmap for membership data products and connects product investments to stated growth, engagement, renewal, retention and member-value objectives.
Runs discovery with Membership, Marketing, CRM, Personalization, Digital Product, Member Care and Finance users to understand decisions, journeys and operational needs.
Owns prioritization across member identity and profile, Member 360, acquisition, onboarding, engagement, lifecycle, renewal, retention, offer, audience, attribution and lifetime-value capabilities.
Defines member and household concepts, lifecycle states, business rules, KPIs, identity requirements, quality thresholds and acceptance criteria in partnership with data governance and domain owners.
Partners with data, engineering and analytics teams to deliver secure, reusable Databricks data products that can support reporting, activation, experimentation, personalization and AI use cases.
Ensures privacy, consent, security and responsible-use requirements are designed into member data products from discovery through operation.
Evaluates opportunities for propensity, churn, next-best-action, segmentation and recommendation capabilities, applying evidence and measurable outcomes before scaling.
Plans launch, activation, stakeholder readiness, communications, training and adoption measurement across the teams and channels that consume membership data.
Measures product performance through adoption, trust, time to activation and movement in the membership outcome each product is intended to support.