Responsibilities
- Snowflake Expertise. Leverage 4-5 years of Snowflake data warehousing experience, including hands-on development in Snowflake Cloud.
- Data Ingestion. Implement and manage data ingestion processes using Snowpipe and other relevant tools to facilitate seamless data flow into the Snowflake ecosystem.
- Snowflake Architecture & Processing. Gain a deep understanding of Snowflake architecture, storage, and processing techniques to optimize database performance.
- Admin & Security Management. Handle Snowflake admin activities such as user roles, permissions, and security best practices.
- SQL & PLSQL Proficiency. Write complex SQL and PLSQL queries, ensuring performance optimization through query tuning, database partitioning, indexing, and other techniques.
- Database Performance Tuning. Monitor and tune query and database performance to ensure optimal efficiency across the Snowflake platform.
- ETL Pipelines. Design, build, and implement efficient ETL pipelines both within and outside the Snowflake environment using SnowSQL, Python, and related tools.
- DBT Development. Develop and maintain DBT models, ensuring effective data transformations for analytics and reporting needs.
- Stored Procedure Development. Create robust stored procedures to automate tasks and optimize data processing.
Mandatory Skills
- Snowflake Data Warehouse. Extensive knowledge of Snowflake’s cloud data platform, including architecture and development.
- Azure Data Factory. Experience in building and managing data pipelines using Azure Data Factory for cloud-based data processing.
- SQL & PLSQL. Proficiency in writing and optimizing SQL queries, with strong skills in SQL query tuning and database performance tuning.
- DBT. Hands-on experience with DBT (Data Build Tool) for data modeling and pipeline development.
- Python. Competency in Python scripting, particularly in designing data pipelines and automation.
- ETL. Expertise in creating and maintaining ETL pipelines, ensuring smooth data integration and transformation workflows.
Nice-to-Have Skills
- Azure Data Bricks. Familiarity with Azure Data Bricks for big data processing and machine learning use cases.
- Azure Data Lake. Experience in managing and integrating data within Azure Data Lake for advanced data storage and analytics.
Key Attributes
- Problem Solver. Strong analytical and troubleshooting skills, particularly in data processing and performance tuning.
- Attention to Detail. Keen focus on optimizing SQL queries and data processing tasks for performance and efficiency.
- Collaboration. Effective communication skills to work closely with cross-functional teams, including data engineers, analysts, and stakeholders.
- Innovation. Passion for exploring new technologies and implementing best practices for data warehousing and analytics.
This role offers an exciting opportunity to work on cutting-edge data warehousing projects with a focus on Snowflake and cloud technologies. If you are a Snowflake expert looking to apply your skills in a dynamic environment, we'd love to hear from you!