About the role
- Design, develop, and maintain scalable data pipelines and data transformation workflows using Snowflake, dbt, SQL, and Python.
- Develop and optimize Snowflake tables, views, queries, stored procedures, and data models.
- Build and maintain dbt models, including incremental models, snapshots, tests, macros, and model dependencies.
- Write complex and optimized SQL queries for data transformation, analysis, and reporting requirements.
- Develop Python scripts and utilities for data processing, automation, and pipeline orchestration.
- Implement data ingestion and transformation processes from multiple source systems into Snowflake.
- Perform data validation, reconciliation, and quality checks to ensure data accuracy and consistency.
- Analyze and optimize Snowflake query performance, warehouse utilization, and data processing efficiency.
- Implement appropriate data modeling techniques, including fact/dimension modeling and Slowly Changing Dimensions (SCD).
- Troubleshoot data pipeline failures and resolve data quality and performance issues.
- Collaborate with data analysts, business stakeholders, and other engineering teams to understand data requirements.
- Follow best practices for code quality, version control, testing, documentation, and deployment.
- 5+ years of experience in Data Engineering
- Strong hands-on experience with Snowflake
- Strong proficiency in SQL
- Hands-on experience with dbt
- Good programming experience in Python
- Strong understanding of ETL/ELT concepts and data pipelines
- Experience with data modeling and database concepts
- Experience with data validation and data quality processes
- Good understanding of Snowflake performance optimization