in modern data engineering practices, cloud technologies and AI/ML integration within the Snowflake ecosystem.

Responsibilities

Design and implement robust data pipelines using Snowflake's native capabilities
Develop and optimize complex queries using Snow SQL and Snow PLSQL
Build scalable data applications with the Snowpark framework and Python
Deploy and manage Snowflake environments across AWS and Azure cloud platforms
Integrate Snowflake with various cloud services, data sources and governance frameworks
Optimize cloud resource utilization and cost management
Maintain data workflows using Apache Airflow and DBT for transformation pipelines
Ensure data quality, reliability and performance across all pipelines
Monitor and troubleshoot data pipeline issues
Leverage Snowflake Cortex AI for advanced analytics and machine learning use cases
Collaborate with data scientists to productionize ML models within Snowflake

Requirements

8 to 15 years of experience in data engineering with a focus on cloud-based data platforms
4+ years of hands-on expertise in Snowflake including Snow SQL, Snow PLSQL and Snowpark
Proficiency in advanced Python programming for data engineering
Skills in AWS and/or Azure cloud services
Experience with Apache Airflow and DBT for workflow orchestration and data modeling
Familiarity with Snowflake Cortex AI's native AI and ML capabilities

Lead Snowflake Data Engineer