Snowflake Data Engineer

Job Overview:

We are seeking a skilled and experienced Snowflake Data Engineer to join our data engineering team. The ideal candidate will be responsible for architecting, designing, and implementing large-scale data intelligence and analytics solutions using Snowflake Cloud Data Warehouse and AWS Redshift. This role requires hands-on expertise in building robust ETL pipelines and managing complex data transformations with tools like Python, Unix scripting, and SnowSQL.

Key Responsibilities:

• Architect and implement scalable data solutions using Snowflake Cloud Data Warehouse.
• Design and develop robust ETL pipelines using Python, SnowSQL, and other data integration tools.
• Write optimized SQL queries for data extraction, transformation, and analysis within Snowflake.
• Develop automation scripts using Unix, Python, or other scripting languages for data extraction, loading, and transformation.
• Provide production support for data warehouse issues including data load failures and transformation discrepancies.
• Translate business intelligence and reporting requirements into database and reporting solutions.
• Understand and implement data transformation and translation logic using appropriate cloud-based tools.
• Work with modern data pipeline automation techniques and cloud-based orchestration tools.
• Document implementations, data flows, and testing protocols clearly for team collaboration and knowledge sharing.
• Collaborate closely with data analysts, architects, and business stakeholders to understand data needs and deliver scalable solutions.

Required Skills & Qualifications:

• Proven experience in Snowflake Cloud Data Warehouse architecture and development.
• Hands-on experience with AWS Redshift and its integration with data pipelines.
• Strong programming and scripting skills in Python, SnowSQL, and Unix.
• Expertise in writing complex and performance-optimized SQL queries.
• Experience in building and managing data pipelines and ETL workflows in cloud environments.
• Solid understanding of data warehouse concepts, dimensional modeling, and data integration best practices.
• Ability to troubleshoot and provide support for data quality and transformation issues.
• Strong analytical and problem-solving skills with a keen eye for performance optimization.
• Excellent verbal and written communication skills.