Snowflake Solutions Engineer

Position Overview

We are seeking an innovative Snowflake Solutions Engineer to join our growing IT team and lead the design and implementation of advanced Snowflake-native applications and AI-powered data solutions. This role will focus on leveraging Snowflake's modern platform capabilities including Streamlit applications, Cortex AI services, and emerging technologies to deliver business value through cutting-edge data solutions. The ideal candidate will have deep expertise in Snowflake's ecosystem, data architecture patterns including data warehousing, data lakes, and open lakehouse architectures, and experience building user-facing data applications.

Essential Functions And Responsibilities

Snowflake Native Application Development (30%)

• 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
• Create reusable application frameworks and component libraries for rapid solution delivery
• 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

Data Architecture and Modern Platform Design (30%)

• 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
• Establish best practices for data organization, storage optimization, and query performance across different data architecture patterns

AI Support and Advanced Analytics Collaboration (15%)

• Support AI and data science teams with Snowflake platform capabilities and best practices
• Collaborate on implementing Snowflake Cortex AI features for business use cases
• Provide technical guidance on data access patterns and feature engineering for AI workloads
• 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

Security, Governance, and Technical Leadership (15%)

• Design and implement role-based access control (RBAC) hierarchies following least privilege principles
• Establish security best practices including network policies, authentication methods, data encryption, and row or column level security and masking
• Implement object tagging strategies and tag-based policies for access control and governance
• Monitor and optimize application performance, query efficiency, and user experience
• Establish cost optimization strategies for compute resources and storage across different workload patterns
• Provide technical guidance on Snowflake capabilities, features, and roadmap to stakeholders
• Lead architectural discussions on solution design patterns and technology selection
• Create technical documentation, implementation guides, and best practice recommendations

Required Qualifications

Education and Experience

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Data Science or related technical field
• At least 2 years of recent hands-on experience with Snowflake platform including advanced features
• Minimum 3 years of experience in data engineering or solutions architecture roles
• 7-10 years of experience in Data Architecture/Engineering and/or BI in a multi-dimensional environment
• Proven track record of developing data applications or analytical solutions for business users

Technical Skills

• Snowflake Expertise: Advanced knowledge of Snowflake architecture including data warehousing, data lakes, and emerging lakehouse features
• Security and Governance: Deep understanding of RBAC, row-level security, data masking, and Snowflake security best practices
• Dev Ops and CI/CD: Strong experience with Git Hub, 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

Preferred Qualifications

Certifications:

• Snowflake Snow Pro Core, Advanced Architect, or Data Engineer certification

AI/ML Collaboration:

• Experience supporting data science teams and understanding ML workflow requirements

Development Frameworks:

• Experience with modern web frameworks, API development, and microservices

Cloud Platforms:

• Knowledge of AWS, Azure, or Google Cloud data…