Snowflake Data Architect

Job Title: Data Architect

About the Role

The Data Architect works in all data environments which includes data design, database architecture, metadata and repository creation. The Data Architect work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.

We are seeking a detail-oriented and results-driven Data Architect. Strong domain knowledge in key practices including data architecture, data integration, master data management, data quality, data modeling and more is essential for this role. This role requires strong ability to collaborate with cross-functional teams, identify defects early in the development cycle, and ensure high-quality product delivery.

Primary Skills

• Snowflake
• Prefect
• Google Cloud Platform
• Azure
• Databricks

Secondary Skills

• data architecture
• data integration
• master data management
• data quality
• data modeling
• API integrations
• ETL
• ELT
• data virtualization
• metadata management
• data lineage
• data stewardship
• regulatory compliance
• enterprise security
• access control

Soft Skills

• collaboration
• technical oversight
• presentation skills

Responsibilities

• Define and maintain enterprise data architecture standards, principles, and roadmaps.
• Design scalable data platforms supporting analytics, reporting, AI/ML, and operational workloads.
• Develop conceptual, logical, and physical data models for enterprise applications.
• Establish architecture patterns for data integration, master data management, and data quality.
• Lead the design and implementation of cloud-based data platforms using technologies such as Snowflake, Prefect, Google Cloud Platform (GCP), Azure and Databricks.
• Define best practices for data storage, processing, orchestration, and security.
• Guide migration of on-premises data assets to cloud environments.
• Architect batch, real-time, and event-driven data pipelines.
• Design solutions for API integrations, ETL/ELT frameworks, and data virtualization.
• Ensure high-performance and scalable ingestion, transformation, and consumption of data.
• Partner with Data Governance teams to establish metadata management, lineage, stewardship, and data quality frameworks.
• Ensure compliance with regulatory requirements including HIPAA, PHI, SOC, and privacy policies.
• Implement enterprise security and access control standards.
• Collaborate with executive leadership, business teams, product owners, and engineering teams to translate business needs into technical solutions.
• Provide architecture guidance and technical oversight throughout project lifecycles.
• Present architecture strategies and roadmaps to senior leadership.