Snowflake Data Engineer - Platform Optimization

Techno Talent Inc.
New York, NY, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Query Performance Amazon Web Services Amazon S3 Apache HTTP Server Cloud Database Cluster Analysis Databases Data Sharing Performance Tuning SQL Databases Snowflake Concurrency
+2 more
Caching Data Pipelines

Job description

We are seeking an experienced Snowflake Data Engineer to support workload optimization, platform performance, resiliency, and cost efficiency. The role will focus on analyzing existing Snowflake workloads, improving resource utilization, and supporting integration with an AWS-based open data platform using Amazon S3, Apache Iceberg, and Apache Polaris., * Design and validate Snowflake integration with Amazon S3, Apache Iceberg, and Apache Polaris.

  • Analyze Snowflake workloads, query performance, warehouse utilization, concurrency, and consumption patterns.
  • Identify and implement performance-tuning and cost-optimization opportunities 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.

Requirements

  • Strong hands-on Snowflake integration with Amazon S3, Apache Iceberg, Apache Polaris, or another Iceberg REST Catalog.
  • Strong hands-on experience with the Snowflake platform, SQL, workload management, and query performance tuning.
  • Experience optimizing virtual warehouses, storage, clustering, caching, concurrency, and Snowflake credit consumption.
  • Knowledge of Snowflake security, access controls, data sharing, monitoring, and operational best practices.
  • Experience troubleshooting complex data pipelines and platform performance issues.
  • Strong understanding of cloud data architecture and integration patterns.

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