Snowflake Data Architect

Primary Responsibilities

• Define and execute the target-state Snowflake architecture supporting enterprise reporting, analytics, and decision-making across key business domains.
• Establish enterprise data modeling standards, architectural patterns, governance frameworks, and golden-source strategies.
• Design scalable logical and physical data models for Project Management, HR, Finance, Accounting, Legal, and Operations data domains.
• Develop and maintain a multi-year enterprise data warehouse and data modernization roadmap aligned with business objectives.
• Design AI-ready data architectures that support both structured and unstructured data for advanced analytics and generative AI use cases.
• Establish Snowflake governance standards including security, cost management, performance optimization, data sharing, monitoring, and observability.
• Design and implement Snowflake Cortex capabilities, including AI SQL, LLM functions, document intelligence, vector functions, and Snowpark solutions.
• Lead the development of scalable data ingestion frameworks integrating enterprise applications such as CMiC, UKG, Salesforce, and other critical systems.
• Oversee enterprise data quality, testing, validation, reconciliation, and observability standards.
• Drive Snowflake performance tuning initiatives through query optimization, clustering strategies, workload management, and concurrency scaling.
• Lead large-scale data warehouse modernization and legacy data migration efforts.
• Partner with business and technology leaders to translate complex requirements into scalable data platform solutions.
• Mentor and guide data engineers, analysts, and data scientists in implementing enterprise data architecture and engineering best practices.

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field required.
• 8+ years of enterprise data architecture, data warehousing, and data platform experience.
• 4+ years of hands-on experience designing and leading Snowflake implementations in cloud production environments.
• Proven experience delivering enterprise-scale data warehouse, analytics, and data transformation programs.
• Deep expertise in Snowflake architecture, including storage and compute separation, micro-partitioning, clustering, performance tuning, governance, and cost optimization.
• Advanced knowledge of dimensional modeling, enterprise data architecture, and data governance best practices.
• Strong SQL development skills and experience with modern ELT/ETL tools such as dbt, Fivetran, SSIS, and orchestration platforms.
• Experience integrating structured and unstructured data sources, including documents, spreadsheets, emails, and PDFs.
• Strong understanding of Microsoft Azure cloud services and enterprise data integration patterns.
• Experience implementing Snowflake Cortex, Snowpark (Python), AI SQL, and AI-driven analytics capabilities in production environments.
• Experience supporting database administration, data migrations, and modernization initiatives.
• Strong leadership, communication, and stakeholder management skills with the ability to present technical strategy to executive audiences.
• Demonstrated ability to mentor technical teams and align data platform strategies with long-term business objectives.
• SnowPro Advanced Certification preferred.
• Experience supporting construction, project-based, HR, finance, accounting, legal, or operations data environments preferred.