Principal Architect - R01571497

15 to 18 years of experience in data architecture and engineering, including extensive expertise in Snowflake and modern data platforms

Key Responsibilities:

• Design and architect scalable, secure, and high-performance Snowflake data solutions to drive enterprise data initiatives.
• Develop and implement robust ETL pipelines using Snowflake Streams, Python, and SQL to enable efficient data ingestion and transformation.
• Optimize Snowflake environments for performance, cost, and reliability by leveraging features such as Time Travel, Fail Safe, and Snowpipe.
• Lead the modeling and structuring of complex Snowflake data warehouses, ensuring data integrity, accessibility, and scalability.
• Configure and manage SnowSQL, stored procedures, and advanced SQL scripts to automate data processing and analytics workflows.
• Collaborate with cross-functional teams to define data platform requirements and deliver modern data solutions aligned with business objectives.
• Troubleshoot and resolve architectural and operational issues within Snowflake and related data platforms, ensuring minimal downtime.
• Mentor and guide junior architects and engineers on best practices in Snowflake engineering and data platform fundamentals.

Required Skills:

• Expertise in Snowflake architecture and engineering
• Advanced proficiency in SQL
• Strong experience with Python for data processing and automation
• Deep understanding of ETL pipeline development
• Hands-on experience with Snowflake Streams for real-time data ingestion
• Proficiency in Time Travel and Fail Safe features within Snowflake
• Implementation and management of Snowpipe for automated data loading
• Skilled in SnowSQL for scripting and data management
• Experience in Snowflake-specific data modeling and warehouse design
• Expertise in developing and managing Snowflake stored procedures

Preferred Skills:

• Experience integrating Snowflake with cloud platforms such as AWS or Azure
• Expertise in advanced data security and governance practices
• Knowledge of performance tuning and optimization for large-scale Snowflake workloads
• Familiarity with emerging data engineering technologies and frameworks
• Experience with orchestration tools for automating data pipelines (e.g., Apache Airflow, dbt)
• Hands-on experience with real-time analytics and streaming data solutions

Desired Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline
• Snowflake SnowPro Advanced Architect certification or equivalent
• Certification in data warehousing or cloud data platform architecture (e.g., AWS Certified Data Analytics, Microsoft Certified: Azure Data Engineer Associate)