Data Engineer (Snowflake)

Job Title: Data Engineer (Snowflake)
Location: Dublin, CA – Hybrid (Onsite Tuesday–Thursday)
Duration: Long-Term Contract
Key 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.

• 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.

• 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.