Data Engineer
3 weeks ago
Job Description:
Snowflake Data Engineer
Must Have: SQL, Python, Snowflake, Data Modelling, ETL, Snowpark
Good to Have: DBT (Data Build Tool), API Integration (AWS Lambda), Git, AWS S3 Integration
Knowledge, Skills and Experience:
- Proficiency in crafting and optimizing complex SQL queries and Stored Procedures for data transformation, aggregation, and analysis within the Snowflake platform.
- Experience with Snowflake cloud data warehousing service, including data loading, querying, and administration.
- Ability to design and implement data models, applying both relational and dimensional modeling techniques, within Snowflake.
- In-depth understanding of ETL processes and methodologies, leveraging Snowflake's capabilities.
- Familiarity with DBT (Data Build Tool) for data transformation and modeling within Snowflake.
- Expertise in integrating Snowflake with AWS S3 storage for data storage and retrieval.
- Proficiency in Snowpark, enabling data processing using Snowflake's native programming language.
- Skill in API integration, specifically integrating Snowflake with AWS Lambda for data workflows.
- Adeptness in version control using GitHub for collaborative code management.
- Adeptness in troubleshooting data-related issues within the Snowflake ecosystem, ensuring data quality and consistency.
- Skill in creating clear and concise technical documentation, facilitating communication and knowledge sharing.
- Designing efficient and well-structured data schemas within Snowflake.
- Utilizing Snowflake's features for data warehousing, scalability, and performance optimization.
- Leveraging Python programming for data processing, manipulation, and analysis in a Snowflake environment.
- Implementing data integration and transformation workflows using DBT.
- Writing and maintaining scripts for data movement and processing, using cloud integration.
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