Data Engineer (Snowflake)

As a Data Engineer, you will be responsible for handling and manipulating data efficiently to support the organization's data needs. Your key responsibilities will include: - Demonstrating 8-12 years of overall professional experience, with a minimum of 7 years focused on data engineering. - Showcasing proven expertise in the Snowflake data warehouse platform, including a deep understanding of its architecture, features, and best practices. - Utilizing expert-level SQL skills for data manipulation, complex query writing, and performance tuning. - Applying extensive experience with ETL/ELT tools and techniques to build scalable data pipelines. - Exhibiting proficiency in at least one scripting language, with Python being highly preferred, for data processing and automation. - Utilizing hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), particularly in data storage services (e.g., S3, ADLS) and computing. - Demonstrating a solid understanding of data warehousing concepts, including Kimball and Inmon methodologies. In addition to the above qualifications, the ideal candidate for this role should have: - 8-12 years of overall professional experience - Minimum of 7 years of hands-on experience in data engineering - Proven, in-depth experience with the Snowflake data warehouse platform - Expert-level SQL skills for data manipulation, complex query writing, and performance tuning - Extensive experience with ETL/ELT tools and techniques - Proficiency in at least one scripting language, preferably Python, for data processing and automation - Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) for data storage and computing - Solid understanding of data warehousing concepts, including Kimball and Inmon methodologies,