Product Manager, Data

SKIMS

Los Angeles (CA)

On-site

USD 165,000 - 180,000

Full time

2 days ago

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Benefits offered by this job

Healthcare (up to 100% company paid)

Fertility benefits

401(k) with up to 4% match

Unlimited PTO

LinkedIn Learning access

Employee discounts

Free weekly catered lunch at HQ

Dog-friendly office

Free swag giveaways

Annual holiday party

Annual summer party

Event invitations and snacks

Job summary

SKIMS is seeking a Product Manager, Data to shape and deliver data products that empower trusted, actionable information across the business. You will translate business needs into a data product strategy, roadmap, and backlog, building scalable capabilities with Data Engineering, Analytics, and teams across Digital, Retail, Merchandising, Planning, Finance, Marketing, Operations, and Technology.

The ideal candidate combines product discipline, technical fluency, and strong business judgment,

Qualifications

Experience defining product roadmaps, backlogs, and delivering cross-functional technical initiatives.
Strong understanding of data warehouses, pipelines, data modeling, BI, and modern analytics workflows.
Working knowledge of SQL and ability to explore data and validate requirements.
Experience with Agile delivery, UAT, and product management tools.
Excellent stakeholder management, facilitation, and written/presentation skills.

Responsibilities

Define and maintain a data product roadmap aligned with SKIMS' priorities.
Identify opportunities to create reusable data assets and self-service capabilities.
Prioritize investments based on value, needs, dependencies, and scalability.
Define outcomes, success criteria, and decision rules for initiatives.
Coordinate with Data Eng, Analytics, and cross-functional teams to deliver backlog items.

Skills

Data product ownership

Roadmap planning

SQL

Agile delivery

Stakeholder management

Communication

Prioritization

Education

Bachelor's degree in business, CS, IS, analytics, or related field

Tools

Snowflake

dbt

Looker

Fivetran

Shopify

NetSuite

Job description

Product Manager, Data

Department: Data, Insights and Loyalty

Employment Type: Full Time

Location: Los Angeles HQ

Compensation: $165,000 - $180,000 / year

Description

SKIMS is a solutions-oriented brand creating the next generation of underwear, loungewear, shapewear, and essentials. We are setting new standards by delivering technically innovative, comfort-driven products with elevated design for everybody.

At the intersection of culture, innovation, and commerce, SKIMS is a global brand redefining modern apparel. Our teams are built on creativity, collaboration, and operational excellence, and we are committed to fostering an inclusive, high-performance environment where ambitious, curious, and values-driven individuals can do the best work of their careers.

As we continue to scale globally, our HQ teams play a critical role in shaping strategy, building world-class infrastructure, and driving sustainable growth across markets.

SKIMS is seeking a Product Manager, Data to shape and deliver data products that make trusted, actionable information available across the business.

This role will translate business needs into a clear data product strategy, roadmap, and prioritized backlog. The Product Manager will focus on scalable, reusable capabilities rather than one-off reporting solutions, ensuring data investments support meaningful business decisions.

The ideal candidate combines product management discipline, technical fluency, and strong business judgment. They will partner closely with Data Engineering, Analytics, Data Science, and teams across Digital, Retail, Merchandising, Planning, Finance, Marketing, Operations, and Technology.

Key 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 clear product outcomes, success measures, and decision criteria for roadmap initiatives.
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 before and during development.
Communicate priorities, trade-offs, scope, and timelines clearly across technical and business teams.

Own the product backlog and partner with Data Engineering, Analytics, and other delivery teams to execute against 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.

Skills, Knowledge and Expertise

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.
Demonstrated 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.

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.

Business and technical teams share a clear, prioritized roadmap for data products and capabilities.
High-value data initiatives are grounded in well-defined user needs and measurable outcomes.
Products are delivered reliably, validated with stakeholders, and adopted in day-to-day business workflows.
Core metrics and data products become more consistent, trusted, accessible, and reusable across teams.
Manual reporting and fragmented solutions decrease as scalable data capabilities mature.
Data investments enable faster, better-informed decisions and measurable business impact.

Benefits, Culture and Perks

Benefits and Culture