Snowflake Data Architect

Title:

Snowflake Data Architect

Location:

Houston, TX

We are seeking a highly skilled Snowflake Data Architect to design and implement scalable, high‑performance data solutions that support advanced analytics and reporting. This role requires deep expertise in data modeling, data warehousing, and Snowflake architecture, along with hands‑on experience integrating semantic models with Power BI or similar BI platforms.

• Architect and develop logical and physical data models within the Snowflake environment to support analytical, reporting, and dashboarding requirements.
• Create and maintain semantic data layers that enable seamless connectivity and optimized performance for Power BI and other visualization tools.
• Lead the end-to-end design and deployment of data warehousing solutions aligned with evolving business needs.
• Perform query optimization, workload tuning, and resource management within Snowflake to ensure peak system performance.
• Define, implement, and monitor data governance policies, security standards, and access controls across the Snowflake platform.
• Partner closely with business stakeholders and analytics teams to translate functional requirements into robust, scalable data architecture designs.
• Provide thought leadership and best practices for Snowflake development, ETL/ELT design, data modeling, and pipeline optimization.

• 12+ years of progressive experience across data engineering, data warehousing, and cloud data architecture roles.
• At least 8+ years in client‑facing positions involving large‑scale data migration, architecture, and solution delivery.
• Advanced proficiency in conceptual, logical, and physical data modeling within the Snowflake platform.
• Strong expertise in data warehousing methodologies and ETL/ELT frameworks.
• Hands‑on experience with Snowflake tuning, resource optimization, clustering, security configuration, and workload management.
• Working knowledge of Power BI or comparable BI platforms, including experience designing semantic data models.
• Strong SQL proficiency and a solid grasp of data governance, data security, and compliance principles.
• Experience working with cloud technologies such as Azure, AWS, or GCP.
• Familiarity with orchestration and pipeline tools such as Airflow, Azure Data Factory, or dbt.
• Ability to thrive in fast‑paced development cycles and adapt to changing project priorities.
• Proven experience collaborating within cross‑functional Agile teams to build and enhance data‑driven and ML‑enabled solutions.
• Experience partnering with data scientists, data engineers, and software teams to support MLOps best practices (CI/CD pipelines, model versioning, monitoring, automated deployment).
• Strong communication skills and the ability to work effectively with globally distributed teams.