Senior Data Architect - Long , 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!

Skin Health Systems’ analytics and data platform spans Snowflake, dbt, Power BI, and multiple ERP, CRM, and SaaS source systems. The Sr Data Architect is the enterprise owner of the architectural standards, data models, and governance frameworks that keep the ecosystem coherent, scalable, and trustworthy. The 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 major data initiatives align with long-term platform strategy.

• 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 architectural standards for BI semantic layers, ensuring alignment between enterprise data models and Power BI consumption layers while standardizing metric definitions and calculation logic.
• Own enterprise data governance architecture including metadata management, data lineage, quality frameworks, and compliance alignment.
• Provide architectural leadership through design reviews, technical guidance, and mentorship across data engineering, BI, and business systems teams.
• Develop and maintain enterprise architecture documentation, reference models, and standardized design patterns; lead architecture review processes for all major data initiatives.
• Perform other duties as assigned.

Required

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 7+ years of experience in data architecture, data engineering, or enterprise data platform roles.
• Strong experience designing enterprise-scale data platforms and analytics architectures.
• Deep expertise in data modeling including conceptual, logical, and dimensional approaches.
• Hands-on experience with cloud data platforms — Snowflake strongly preferred; AWS, Azure, or GCP acceptable.
• Strong understanding of modern data transformation tools such as dbt or equivalent.
• Experience designing data integration patterns across multiple enterprise systems.
• Experience working with BI semantic layers such as Power BI datasets or…