Snowflake Architect

Overview Protege Hunters has an immediate direct hire opportunity available for a Snowflake Solutions Engineer/Architect. The ideal candidate will bring passion and innovation to lead a growing IT Team and will have deep expertise in Snowflake's ecosystem, data architecture patterns including data warehousing, data lakes, and experience building user-facing data applications. If you are a Snowflake Architect and have a proven track record that includes a blend of expertise in cloud data warehousing, enterprise data architecture, and deep knowledge of Oracle's suite of applications as well as designs, implementations, and have optimized multiple Snowflake data platforms to meet business requirements for scalable, secure, and efficient data storage and retrieval, then we want to speak with you! Mandatory Qualifications 8+ years in data warehousing and enterprise data architecture, with significant hands-on experience (4+ years) on the Snowflake platform. Expertise in Snowflake's architecture Snowflake Expertise: Advanced knowledge of Snowflake architecture including data warehousing, data lakes, and emerging lakehouse features 7-10 years of experience in Data Architecture/Engineering and/or BI in a multi-dimensional environment 3 plus years of recent hands-on experience with Snowflake platform including advanced features Proven track record of developing data applications or analytical solutions for business users Security and Governance: Deep understanding of RBAC, row-level security, data masking, and Snowflake security best practices DevOps and CI/CD: Strong experience with GitHub, SnowDDL, automated deployment pipelines, and infrastructure as code Application Development: Proficiency with Snowflake Streamlit for building interactive data applications SQL Proficiency: Expert-level SQL skills with experience in complex analytical queries and optimization Python Programming: Strong Python skills for Snowpark development, data processing, and application logic Data Architecture: Deep understanding of data warehousing concepts, data lake patterns, and modern lakehouse architectures Backup and Recovery: Experience with disaster recovery planning, backup automation, and data retention strategies Must have a Deep understanding of the Snowflake Data Cloud platform, including its features and capabilities. Must have Extensive experience with data migration from legacy platforms, building robust ETL/ELT pipelines, and ensuring seamless data flow. Advanced proficiency in SQL for data manipulation and querying. 7 plus years experience in designing and managing data pipelines and ETL processes. Hands on experience as a Lead that executed multiple complex migrations from legacy systems to Snowflake and the ability to provide technical direction, mentor junior team members, and act as a trusted advisor. In addition Must have Cloud Platforms: Familiarity with cloud environments like AWS, Azure, and GCP for integrated solutions. Excellent Communication skills to work effectively with cross-functional teams, including business stakeholders, data engineers, and security teams. Responsibilities Architecture Design: Design and develop interactive data applications using Snowflake Streamlit for self-service analytics and operational workflows that enable business users to interact with data through intuitive interfaces Data warehouse architectures within Snowflake to support business goals. Design and architect data solutions: Design and implement scalable, high-performance data architectures on Snowflake Integrate Snowflake Native Apps and third-party marketplace applications to extend platform capabilities Develop custom UDFs and stored procedures to support advanced application logic and business rules Design and implement modern data architecture solutions spanning data warehousing, data lakes, and lakehouse patterns Implement and maintain medallion architecture (bronze-silver-gold) patterns for data quality and governance Evaluate and recommend architecture patterns for diverse use cases including structured analytics, semi-structured data processing, and AI/ML workloads Data Modeling: Translate business requirements into scalable and secure data models. Design data structures and access patterns optimized for ML model training and inference Participate in proof-of-concepts for AI capabilities and provide platform expertise Design and implement role-based access control (RBAC) hierarchies following least privilege principles Performance Optimization: Ensure optimal data storage, retrieval, and overall performance of the Snowflake environment. Migration: Lead and execute complex migrations from legacy systems to Snowflake. Security and Compliance: Design and implement security models, ensuring data integrity and compliance with standards and regulations. Create technical documentation, implementation guides, and best practice recommendations How to Apply Forward Resumes to View email address on click.appcast.io #J-18808-Ljbffr