Snowflake Data Engineer

Job description

**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