Data Solutions Architect
$170,000–$180,000 year
Remote · United States
Job Summary
Data Solutions Architect at MANSCAPED responsible for owning the architecture and evolution of the Snowflake data environment, establishing data modeling standards across core domains, designing schemas and datasets to support BI, analytics, reporting, and future AI-enabled use cases; developing and maintaining complex SQL queries, stored procedures, and performance-optimized data structures; optimizing Snowflake performance and cost; enforcing RBAC and security standards; partnering with Technology, Security, and Analytics stakeholders on identity management and governance; establishing row-level security, masking policies, and data quality practices; leading data pipeline architecture and data-product development; collaborating with BI and enterprise teams to ensure reliable, governance-aligned data models for Looker and self-service reporting; driving a single source of truth through well-documented data structures and reusable data products; communicating complex technical topics to stakeholders and advising on risks, dependencies, and long-term data-architecture priorities; and performing other duties as required.
Required Qualifications
- 10+ years of experience in data architecture, analytics engineering, data warehousing, data platform leadership, or enterprise data solutions
- Deep hands-on experience with Snowflake, including architecture design, schema development, performance optimization, RBAC, views, SQL, and stored procedures
- Strong experience building and scaling modern data warehouse and ETL/ELT environments
- Experience designing robust data models for BI, analytics, executive reporting, and cross-functional business use
- Proven ability to establish data governance, access control, and data quality frameworks in complex business environments
- Experience partnering with Technology, Security, Infrastructure, BI, and business teams
- Strong understanding of data pipeline architecture, source-system mapping, transformation logic, and downstream reporting needs
- Familiarity with AI-ready data architecture, natural-language query interfaces, or AI-assisted analytics workflows
- Experience with consumer, Ecommerce, retail, marketplace, subscription, wholesale, or omnichannel data environments
- Strong analytical, debugging, and problem-solving skills
- Ability to simplify complex technical topics for non-technical stakeholders
- Excellent communication, stakeholder-management, and cross-functional leadership skills
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