- Experience in data engineering, specifically with Snowflake and DBT.
- Key skills required are strong hands-on experience with DBT
- expertise in building and managing data models using DBT commands, Jinja macros, and configurations, and proficiency in developing and managing DBT projects, testing, and documentation.
- Robust SQL proficiency, including advanced concepts, is essential.
- Experience with Snowflake's architecture and optimizing SQL queries for the platform is also necessary. · A solid understanding of data warehousing architectures and ETL/ELT processes, data transformation,
and quality is expected. ·
Proficiency with cloud platforms like AWS, Azure, or GCP and experience with version control systems like Git are often required. ·
Roles and Responsibilities
- Design, develop, and optimize data models and transformations using DBT
- Build and manage ELT (Extract, Load, Transform) pipelines using DBT and other tools
- Ensure data quality and integrity through testing and validation
- Collaborate with data engineers, analysts, and other stakeholders
- Optimize Snowflake (or other data warehouse) performance and cost
- Drive data architecture decisions and implement best practices