Title: Snowflake Data Architect

Location: Dallas, TX - Atlanta, GA or Richmond, VA - Hybrid

Contract: 12-month

No H1B

Job Summary: We are seeking an experienced Snowflake Data Architect to lead the design and implementation of scalable enterprise data warehouses (EDW) while establishing strong ontology and taxonomy frameworks. The ideal candidate will have deep expertise in data modeling, metadata management, and data governance to ensure seamless data integration and accessibility across the organization.

Enterprise Data Warehouse (EDW) Design & Modeling

Required Qualifications:

• 15+ years of experience in data architecture, data modeling, and data governance.
• 5+ years of hands-on experience designing and implementing Snowflake-based data solutions.
• Strong expertise in dimensional modeling (Kimball/Inmon).
• Proven experience in ontology and taxonomy design, preferably in enterprise environments.
• Proficiency in SQL, Python, and dbt (Data Build Tool) for data modeling and transformations.
• Experience with metadata management tools (e.g., Collibra, Alation, Atlan) and data catalogs.
• Knowledge of cloud-based architectures (Azure) and integration with Snowflake.
• Understanding of data privacy, security frameworks (GDPR, CCPA, HIPAA), and access controls.
• Strong problem-solving skills and the ability to communicate complex technical concepts to business users.

Architect, develop, and optimize data warehouse solutions in Snowflake for large-scale enterprise applications.

Design and implement dimensional and relational data models, ensuring scalability, efficiency, and maintainability.

Define best practices for schema design, partitioning, clustering, and indexing in Snowflake.

Develop ETL/ELT pipelines in collaboration with data engineers to streamline data ingestion and transformation processes.

Ontology and Taxonomy Development

Define and implement ontology frameworks to establish relationships between data entities.

Develop and manage data taxonomies to standardize data classification and metadata organization.

Collaborate with business stakeholders to create a semantic layer that improves data discoverability and usability.

Ensure alignment with industry standards (e.g., FIBO, CDISC, schema.org) for data classification.

Metadata Management & Data Governance

Implement data cataloging solutions to enhance metadata documentation and lineage tracking.

Define data governance policies, including data security, access controls, and compliance.

Work closely with data stewards, analysts, and engineers to ensure consistent data definitions and quality across the organization.

Establish automated workflows for data classification, tagging, and access provisioning.

Performance Optimization & Best Practices

Optimize Snowflake compute and storage costs through clustering strategies, caching, and workload management.

Implement monitoring tools to track query performance, storage consumption, and concurrency.

Advocate for CI/CD practices, Infrastructure as Code (IaC), and automation in Snowflake deployments.