Snowflake Data Architect

Summary

Join The Motley Fool as a Freelance Data Architect specializing in Snowflake! This is a mid to senior-level, 100% remote position (US-based candidates only) requiring 4-5+ years of experience. You will focus on re-architecting and optimizing our reporting layer in Snowflake, improving cost efficiency and compute optimization. The role involves collaborating with data engineers and stakeholders to implement optimizations, enhance query performance, and reduce data processing time. Strong analytic engineering skills and a deep understanding of Snowflake's architecture are essential. The contract is for at least 6 months, 40 hours per week.

Requirements

• Proven experience working with Snowflake data warehouse, including optimization projects
• Strong expertise in analytic engineering techniques within Snowflake, such as query optimization, indexing, and partitioning
• Deep understanding of Snowflake's architecture, including virtual warehouses, storage optimization, and clustering keys
• Proficiency in SQL and data modeling for Snowflake
• Familiarity with ETL processes and data pipeline optimization
• Excellent problem-solving skills and the ability to troubleshoot complex performance issues
• Strong communication skills to collaborate with cross-functional teams and stakeholders
• Self-motivated with a proactive approach to identifying and implementing optimizations

Responsibilities

• Evaluate and optimize the reporting layer of our Snowflake data warehouse to enhance cost efficiency and compute utilization
• Develop and implement strategies to improve query performance, reduce data processing time, and enhance overall efficiency
• Collaborate closely with the data engineering team to implement optimizations without compromising data integrity or security
• Utilize advanced analytic engineering techniques within Snowflake to optimize data transformations and computations
• Design efficient data models and schemas to support optimized reporting and analytics
• Implement best practices for data loading, storage, and retrieval to minimize costs and maximize performance
• Optimize query performance by tuning Snowflake configurations and query execution plans
• Implement caching strategies and materialized views to improve response times for commonly used reports
• Collaborate with data engineers to ensure efficient ETL processes and data transformations

Benefits

$85 — $100 USD