Associate Manager, Data Product

About the Company

e.l.f. Beauty, Inc. stands with every eye, lip, face and paw. Our deep commitment to clean, cruelty free beauty at an incredible value has fueled the success of our flagship brand e.l.f. Cosmetics since 2004 and driven our portfolio expansion. Today, our multi-brand portfolio includes e.l.f. Cosmetics, e.l.f. SKIN, pioneering clean beauty brand Well People, Keys Soulcare, a groundbreaking lifestyle beauty brand created with Alicia Keys and Naturium, high-performance, biocompatible, clinically-effective and accessible skincare.

In our Fiscal year 25, we had net sales of $1 Billion and our business performance has been nothing short of extraordinary with 26 consecutive quarters of net sales growth. We are the #2 mass cosmetics brand in the US and are the fastest growing mass cosmetics brand among the top 5. Our total compensation philosophy offers every full-time new hire competitive pay and benefits, bonus eligibility (200% of target over the last four fiscal years), equity, and a hybrid 3 day in office, 2 day at home work environment. We believe the combination of our unique culture, total compensation, workplace flexibility and care for the team is unmatched across not just beauty but any industry.

Visit our Career Page to learn more about our team: 

Position Summary

This person will be a detail-oriented and technically adept Data Product Manager to support the infrastructure powering our MMM, CDP, and other data products. This person will play a critical role in maintaining our data science models, documenting our data infrastructure, and ensuring that governance of data for these tools is upkept. 

• Partner with data science and marketing teams to ensure data used in MMM is accessible and documented.
• Maintain data pipelines and tables in Snowflake to support MMM.
• Serve as a key partner to marketing and analytics teams for segmentation, personalization, and experimentation support.

• Maintain, monitor, and retrain marketing data science models in Snowflake, supporting use cases like churn prediction, CLTV, and replenishment.
• Work closely with the data team to operationalize and validate models used in CRM execution.
• Support the maintenance and refresh of MMM, ensuring all data sources are accounted for.

• Own and manage the CRM Data Dictionary, ensuring all data elements, definitions, sources, and usage guidelines are clearly documented.
• Create and enforce documentation standards that scale with our growing tech stack and use case complexity.
• Act as a power user of our CDP and MMM platform, supporting execution of identity resolution strategies, building audiences, and managing schema changes.

• Help scope and manage ad hoc or new data product requests related to marketing measurement or customer data.

• Establish and maintain quality assurance processes to ensure data integrity across platforms and workflows.
• Support data compliance efforts, including GDPR/CCPA requirements related to marketing data

• Detail-oriented and technically adept professional with experience in managing marketing and data science infrastructure.
• Strong understanding of Snowflake, data pipelines, and marketing measurement tools such as MMM and CDP.
• Proven ability to collaborate cross-functionally with marketing, analytics, and data teams.
• Experience maintaining and operationalizing data science models (e.g., churn prediction, CLTV, replenishment).
• Knowledge of data governance, documentation standards, and compliance frameworks (GDPR/CCPA).
• Excellent organizational, documentation, and communication skills to manage complex data environments.

This job description is intended to describe the general nature and level of work being performed in this position. It also reflects the general details considered necessary to describe the principal functions of the job identified, and shall not be considered, as detailed description of all the work required inherent in the job. It is not an exhaustive list of responsibilities, and it is subject to changes and exceptions at the supervisors' discretion.

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