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 - Bachelor's or master's degree in computer science, data engineering, or a related field. - 7+ years of experience as a Snowflake developer or data engineer with a focus on data warehousing and ETL. - Snowflake certification(s) is a plus. - Strong SQL skills and proficiency in data modeling and database design. - Knowledge of cloud data warehousing concepts and best practices. - Familiarity with data integration tools and technologies. - Solid understanding of data governance, data security, and compliance requirements. - Experience with version control systems and deployment processes. - Excellent problem-solving and troubleshooting skills. - Strong communication and collaboration abilities. - Ability to work in an Agile or iterative development environment.
| Skill | Required / Desired | ||
| Snowflake Data Warehouse Design & Development | Required | ||
| Cloud Computing, Preferably AWS (Azure, Google Cloud Platform-) | Required | ||
| Data Modeling (Star Schema, Snowflake Schema) | Required | ||
| Continuous Integration/Deployment (CI/CD) Tools | Required | ||
| Performance Tuning & Optimization | Required | ||
| SQL for Data Querying & Manipulation | Required | ||
| Data Migration to Cloud Platforms | Required | ||
| Data Security & Governance in Cloud Environments | Required | ||
| Data Warehousing Best Practices | Required | ||
| Automation using Python/SnowSQL | Required | ||
| ETL/ELT Processes using Snowflake | Required | ||
| Snowflake Stored Procedures, UDFs, and Views | Required | ||
| Working with Snowflake Utilities (SnowPipe, Streams, Tasks) | Required | ||
| Data Integration (Informatica, Talend, Matillion, DBT - Preferable) | Highly desired | ||
| Bachelor's Degree minimum | Required |
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