Job Description
Design, implement, and optimize data solutions using the Snowflake cloud data platform. This role plays a pivotal part in architecting data warehouses, data lakes, and ETL processes to enable efficient data storage, processing, and analytics for the DOE.
A Senior Snowflake Developer is a highly skilled professional responsible for designing, implementing, and optimizing data solutions using the Snowflake cloud data platform. This role plays a pivotal part in architecting data warehouses, data lakes, and ETL processes to enable efficient data storage, processing, and analytics for the organization.
Responsibilities
1. Data Architecture
- Collaborate with data architects to design and develop Snowflake data models and schemas.
- Create and maintain a well-structured data warehouse and data lake architecture.
2. Data Integration
- Develop ETL (Extract, Transform, Load) processes to ingest data from various sources into Snowflake.
- Ensure data integration processes are efficient, reliable, and scalable.
- Design and implement data pipelines using Snowflake features like tasks and streams.
3. Performance Optimization
- Optimize query performance by creating and maintaining appropriate indexes, materialized views, and clustering keys.
- Identify and resolve performance bottlenecks in data processing.
4. SQL Development
- Write complex SQL queries, stored procedures, and user-defined functions (UDFs) to support data analytics and reporting needs.
- Ensure SQL code follows best practices for readability and performance.
5. Security and Access Control
- Implement and manage security measures, including role-based access control (RBAC) and data encryption, to protect sensitive data.
- Audit and monitor data access and user activities.
6. Data Quality Assurance
- Define and implement data quality checks and validation processes to maintain data accuracy.
- Establish data quality rules and alerts to proactively identify issues.
7. Documentation
- Create and maintain technical documentation for data models, ETL processes, and data dictionaries.
- Document best practices, standards, and guidelines for Snowflake development.
8. Version Control and Deployment
- Use version control systems (e.g., Git) for managing Snowflake SQL scripts and objects.
- Coordinate the deployment of changes to Snowflake environments.
9. Monitoring and Alerts
- Set up monitoring and alerting for Snowflake environments to proactively detect and respond to issues.
- Troubleshoot and resolve incidents related to data processing and performance.
10. Backup and Recovery
- Implement backup and recovery strategies to ensure data integrity and availability.
- Develop and test data recovery procedures.
11. Collaboration
- Collaborate with data engineers, data scientists, and business analysts to understand data requirements and provide data solutions.
- Work with cross-functional teams to support data-related projects and initiatives.
Qualifications
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