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Snowflake Data Engineer – Platform Optimization

Techno Talent Inc.New York, NY🇺🇸United StatesPosted 3 Sept 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
Yesterday
SQLAWSSnowflakeApacheRESTdbt

Job Description

Title: Snowflake Data Engineer – Platform Optimization
Location : New York, NY
Work Type: Hydrid/Remote
 
 
 
Snowflake Data Engineer – Platform Optimization
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.
Key Responsibilities
  • 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.
Required Skills
  • 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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