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Metro location and popular Data Engineer title increase competition despite Snowflake specialization.
Snowflake- and dbt-specific expertise and cloud experience make cross-industry transferability limited.
Explicit 7+ years and mandatory Snowflake, SQL, Python, Snowpark, cloud and dbt create stringent filters.
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Design, develop, and maintain scalable ELT/ETL data pipelines and workflows within Snowflake using SQL, Python, Snowpark, and dbt.
Optimize Snowflake performance and cost efficiency through query tuning, warehouse sizing, clustering, and workload management.
Implement orchestration, dependency management, monitoring, error handling, and recovery mechanisms while collaborating with architects and other teams to deliver production-ready data solutions.
7+ years of hands-on Data Engineering experience with significant Snowflake expertise.
Advanced SQL skills including complex transformations, query optimization, and stored procedures; strong Python development experience.
Experience with Snowpark, Dynamic Tables, Streams, Tasks, and building production-grade ELT/ETL pipelines.
Experience with at least one major cloud platform (AWS, Azure, or GCP) and modern software development practices including Git, CI/CD, and automated testing.
Proven ability to modernize and optimize data pipelines focusing on Snowflake performance and cost management.
Strong experience implementing scalable data architectures with orchestration and dependency management in cloud environments.
Comfortable working in hybrid remote setup collaborating with cross-functional teams for Agile delivery and production deployments.