Product Manager, Data

Skims•Los Angeles, CA

About The Position

SKIMS is seeking a Product Manager, Data to shape and deliver data products that make trusted, actionable information available across the business. The role translates business needs into a clear data product strategy, roadmap, and prioritized backlog, with an emphasis on scalable, reusable capabilities rather than one-off reporting solutions. The Product Manager ensures data investments support meaningful business decisions and partners closely with Data Engineering, Analytics, Data Science, and teams across Digital, Retail, Merchandising, Planning, Finance, Marketing, Operations, and Technology. The role owns product strategy, discovery, delivery, lifecycle management, data quality, governance, stakeholder partnership, and adoption. Success includes a shared, prioritized roadmap; reliable products grounded in user needs and measurable outcomes; trusted, consistent, accessible, reusable data capabilities; reduced manual reporting and fragmented solutions; and faster, better-informed decisions with measurable business impact.

Requirements

4+ years of experience in product management, technical product management, data and analytics, or a related field, including ownership of data or analytics products.
Experience defining product roadmaps, managing backlogs, and delivering cross-functional technical initiatives.
Strong understanding of data warehouses, pipelines, data modeling, business intelligence, and modern analytics workflows.
Working knowledge of SQL and the ability to independently explore data and validate business requirements.
Ability to translate complex business needs into actionable technical specifications.
Experience with Agile delivery practices, user acceptance testing, and product management tools.
Excellent stakeholder management, facilitation, written communication, and presentation skills.
Strong analytical judgment and ability to prioritize competing needs in a fast-moving environment.
Bachelor’s degree in business, computer science, information systems, analytics, or a related field, or equivalent practical experience.

Nice To Haves

Experience within apparel, fashion, beauty, retail, ecommerce, or another consumer-facing business.
Familiarity with Snowflake, dbt, Looker, Fivetran, or comparable modern data technologies.
Experience with Shopify, NetSuite, ERP, merchandising, planning, or other enterprise source systems.
Understanding of omnichannel sales, customer, product, inventory, and marketing data domains.
Experience building governed metrics, semantic layers, master data capabilities, or self-service analytics products.
Exposure to data governance, data quality, forecasting, experimentation, or AI/ML-enabled products.

Responsibilities

Define and maintain a data product roadmap aligned with SKIMS’ strategic and operational priorities.
Identify opportunities to create reusable data assets, standardized metrics, and self-service capabilities across business functions.
Prioritize investments based on business value, user needs, technical dependencies, and long-term scalability; define outcomes, success measures, and decision criteria.
Balance immediate stakeholder needs with sustainable platform and product development.
Partner with business stakeholders to understand workflows, decisions, pain points, and unmet data needs.
Translate ambiguous requests into product requirements, user stories, acceptance criteria, and clear definitions of success.
Facilitate alignment on business rules, metric definitions, source-system requirements, and intended user experiences; validate proposed solutions with users.
Communicate priorities, trade-offs, scope, and timelines across technical and business teams.
Own the product backlog and partner with Data Engineering, Analytics, and other delivery teams to execute the roadmap.
Coordinate dependencies across data sources, integrations, models, semantic layers, and reporting experiences.
Lead business validation, user acceptance testing, release readiness, and stakeholder enablement.
Monitor delivered capabilities and drive enhancements based on usage, feedback, and changing business needs.
Identify delivery risks early and support pragmatic decisions that protect product quality and value.
Champion consistent business definitions, clear ownership, documentation, and discoverability of data products.
Partner with technical teams to define expectations for data quality, reliability, freshness, and issue resolution.
Support scalable data models, governed metrics, and intuitive self-service analytics experiences.
Help reduce fragmented reporting and manual reconciliation through shared enterprise data capabilities.
Build trusted relationships across Ecommerce, Retail, Merchandising, Planning, Finance, Marketing, and Operations.
Lead working sessions that connect business priorities to data product decisions and delivery plans.
Drive adoption through communication, training, documentation, and ongoing stakeholder feedback.
Measure product impact through usage, user satisfaction, reduced manual effort, and improved decision-making.
Promote a product-led, customer-focused approach to data across SKIMS.