Snowflake Data Engineer
Summary
Builds and maintains Snowflake data pipelines and warehouses, focusing on Data Vault design and performance tuning for scalable analytics.
The Snowflake Data Engineer will be a member of the data engineering team for creating a data vault and data warehouse on Snowflake. This role will focus on building and maintaining scalable, efficient, and reliable data pipelines using the Snowflake Data Cloud. The ideal candidate will have extensive knowledge of Snowflake's architecture, features, and best practices.
Responsibilities
- Design, build, and maintain efficient, scalable, and reliable data pipelines using Snowflake and other relevant data integration tools.
- Collaborate with data architects, analysts, and business stakeholders to understand data needs and deliver end-to-end solutions.
- Optimize and performance‑tune Snowflake data processes using best practices such as clustering keys, materialized views, and caching.
- Ensure data quality, accuracy, and security by implementing proper validation, monitoring, and access controls.
- Monitor data processing operations to ensure timely and successful completion, and proactively troubleshoot any issues.
- Stay updated with the latest Snowflake features, upgrades, and best practices to continually improve data processes.
- Translate complex functional and technical requirements into detailed designs.
- Contribute to the team's knowledge by providing guidance, conducting code reviews, and sharing expertise.
Requirements
- Minimum of 3 years of experience as a Data Engineer or similar role with hands‑on experience with Snowflake.
- Strong SQL skills and experience with Snowflake utilities like SnowSQL, SnowPipe, and SnowPark.
- Familiarity with data modeling concepts and ETL processes.
- Data Vault 2.0
- Kimball Data Marts
- Snowflake SnowPro certification.
- Familiarity with scripting languages like Python.
- Strong problem‑solving skills and attention to detail.
- Excellent communication and collaboration skills.