Snowflake with PySpark - Lead

Snowflake Data Warehouse:

·       Design, implement, and optimize data warehouses on the Snowflake platform.

·       Ensure effective utilization of Snowflake features for scalable and high-performance data storage.

Data Pipeline Development:

·       Develop, implement, and optimize end-to-end data pipelines on Snowflake.

·       Create and maintain ETL workflows for seamless data processing.

Data Transformation with PySpark:

·       Leverage PySpark for advanced data transformations within the Snowflake environment.

·       Implement data cleansing, enrichment, and validation processes using PySpark.

Requirements:

·       Proven experience as a Data Engineer, with a strong emphasis on Snowflake.

·       Proficiency in Snowflake features and capabilities for data warehousing.

·       Expertise in PySpark for data processing and analytics is a must.

·       Experience with data modeling, ETL processes, and efficient data storage.

·       Proficiency in programming languages such as Python, SQL, or Scala for data processing.

Skills:

Snowflake, PySpark