Snowflake Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using DBT, Snowflake, and Python
• Build and manage data transformation workflows using DBT (models, macros, testing, and documentation)
• Develop efficient data ingestion and processing pipelines using Python
• Optimize Snowflake data models, queries, and performance for large-scale datasets
• Ensure data quality, reliability, and consistency through testing and validation frameworks
• Collaborate with data analysts, business teams, and stakeholders to understand data requirements
• Implement best practices for data modeling, version control, and pipeline orchestration
• Monitor and troubleshoot data pipeline issues and performance bottlenecks
• Maintain clear and structured documentation for data workflows and pipelines

Required Skills & Qualifications

• 57 years of hands-on experience in Data Engineering
• Strong expertise in DBT (Data Build Tool)
• Solid experience with Snowflake (data warehousing, performance tuning, optimization)
• Strong/Expert Python skills for data processing and pipeline development
• Good understanding of SQL and data modeling concepts (star schema, dimensional modeling)
• Experience with data pipeline orchestration tools (Airflow or similar)
• Familiarity with data quality and testing frameworks
• Strong problem-solving and analytical skills

Preferred Qualifications

• Experience working in cloud environments (AWS, Azure, or GCP)
• Familiarity with CI/CD practices for data pipelines
• Exposure to real-time or streaming data pipelines is a plus
• Experience in enterprise-scale data platforms

Key Deliverables

• Robust and scalable data pipelines
• Optimized Snowflake data models and queries
• DBT-based transformation frameworks
• High-quality, reliable datasets for analytics and reportin