Senior Data Architect - Long Beach, CA

About Us Hydrafacial is a global category-creating company focused on bringing innovative products to market and delivering beauty health experiences by reinventing our consumer’s relationship with their skin, their bodies and their self-confidence. Every person here is a key player in our success.  We are firm believers in making the little things count each day so the big things will follow. If this sounds like you, come check us out! This is the perfect opportunity to work with some of the best leaders in the industry while you gain the global and strategic experience to add to your professional toolbox.   Job Description: WHY THIS ROLE MATTERS SkinHealth Systems' analytics and data platform spans Snowflake, dbt, Power BI, and multiple ERP, CRM, and SaaS source systems — and the Sr Data Architect is the enterprise owner of the architectural standards, data models, and governance frameworks that make that ecosystem coherent, scalable, and trustworthy. This role defines how data is ingested, transformed, stored, and consumed across the organization, providing architectural leadership to data engineering, BI, and business systems teams to ensure every major data initiative aligns with long-term platform strategy. WHAT YOU’LL DO Define and maintain the enterprise data architecture blueprint across operational and analytical domains, ensuring alignment between business strategy, data capabilities, and technology platforms. Establish and govern architecture standards for modern data platforms including Snowflake, dbt, and associated integration layers — ensuring consistency in how data is ingested, transformed, stored, and consumed. Design scalable, reusable architecture patterns that support analytics, reporting, and BI consumption, optimized for performance, maintainability, and enterprise-wide reuse. Lead the development of the enterprise data platform roadmap, translating business growth, modernization initiatives, and emerging analytics requirements into a coherent architectural evolution strategy. Define enterprise-wide conceptual, logical, and dimensional data models across key business domains, ensuring consistency in how data entities, relationships, and metrics are structured across systems. Establish canonical definitions for critical business entities and metrics, ensuring a single source of truth for reporting, analytics, and decision-making across all functional areas. Design and standardize dimensional modeling approaches — facts, dimensions, and data marts — that support both operational reporting and advanced analytics use cases. Define integration architecture patterns across ERP, CRM, SaaS, APIs, and internal applications, ensuring data is reliably and securely ingested and made available across operational and analytical environments. Architect batch and near real-time data ingestion frameworks; define best practices for transformation architecture within Snowflake and dbt. Establish…