Data Engineer (Snowflake)

Data Engineer (Snowflake)Location: Dublin, CA – Hybrid (Onsite Tuesday–Thursday) Duration: Long-Term ContractKey Responsibilities:Design, develop, and implement data engineering solutions using Snowflake, Azure, Python, and SQL.Build and optimize Snowflake solutions, including data processing, warehouse sizing, query optimization, and performance tuning.Troubleshoot Snowflake queries and platform issues using query history, query plans, and performance diagnostics.Develop Python-based solutions, automation scripts, prototypes, and tools to support data engineering and platform operations.Write, optimize, and troubleshoot complex SQL queries and stored procedures.Leverage Azure services and capabilities to build and support data engineering solutions within the Azure ecosystem.Research emerging technologies and evaluate new Snowflake capabilities for potential adoption.Develop and execute POCs to validate technical approaches against business requirements and use cases.Assess technical limitations, trade-offs, performance, and scalability before recommending solutions.Experiment with AI technologies, AI agents, and AI-driven automation to identify opportunities within the data platform environment.Perform root-cause analysis, troubleshoot production issues, and provide occasional L2/L3 production support.Required Qualifications:7+ years of overall IT experience, including 5+ years working with data platforms.Strong hands-on Snowflake engineering and development experience.Solid understanding of Snowflake architecture, warehouse sizing, query history, query plans, performance tuning, and optimization.Strong hands-on Microsoft Azure experience and understanding of data engineering within the Azure ecosystem.Strong Python development skills, including automation, solution development, and prototyping.Advanced SQL skills, including query development, troubleshooting, stored procedures, and platform diagnostics.Experience researching unfamiliar technologies, building POCs, and evaluating technical solutions independently.Strong analytical, troubleshooting, and root-cause analysis skills.Ability to work through ambiguity and provide occasional production support.Preferred Qualifications:Hands-on experimentation with AI technologies, AI agents, or AI-driven automation.Experience applying AI capabilities within data engineering or data platform environments.Experience evaluating new platform features and recommending technology adoption based on technical findings.Strong problem-solving skills and the ability to independently develop and validate technical solutions.