Snowflake Data Engineer Platform Optimization

Our client is seeking an experienced Snowflake Data Engineer to optimize and stabilize their cloud data platform. You will design integrations, tune performance, reduce costs, and establish best practices across Snowflake and AWS infrastructure.

Responsibilities & Qualifications

• Design and validate Snowflake integrations with Amazon S3, Apache Iceberg, and Apache Polaris
• Analyze workloads, query performance, warehouse utilization, and consumption patterns to identify optimization opportunities
• Implement performance-tuning and cost-optimization strategies across databases, warehouses, pipelines, and dbt workloads
• Review platform incidents and workload failures to improve reliability, resiliency, monitoring, and operational controls
• Support workload benchmarking and placement assessments across Snowflake and AWS services
• Establish optimization recommendations, platform guardrails, and measurable cost-efficiency improvements
• Troubleshoot data pipeline issues and ensure compliance with Snowflake security and access control standards
• Monitor platform health and recommend operational best practices for credit consumption and concurrency management

Requirements

• 8–10 years of data engineering and cloud platform experience
• Expert-level proficiency with Snowflake platform architecture, SQL, and workload management
• Hands-on experience with query performance tuning, virtual warehouse optimization, clustering, and caching strategies
• Strong knowledge of storage optimization, credit consumption analysis, and concurrency management
• Proven expertise in Snowflake security, access controls, and data sharing configurations
• Solid understanding of cloud data architecture and integration patterns with AWS services
• Demonstrated ability to monitor systems, troubleshoot complex issues, and implement operational improvements
• Experience designing and validating integrations with Apache Iceberg, Apache Polaris, and S3-based data lakes