Data Engineer
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Summary
A Snowflake-focused data engineer who builds and maintains ELT pipelines into the Snowflake Data Cloud, writes advanced SQL and stored procedures, designs dimensional data models, tunes performance, and handles security and cloud migrations. Core tech includes Snowflake (Snowpipe, Streams, Tasks, Snowpark), SQL, Python or Scala, AWS/Azure/GCP, and tools like dbt, Fivetran, or Informatica.
A Snowflake Developer builds, optimizes, and manages cloud-based data warehouses and data pipelines using the Snowflake Data Cloud platform.
Core Responsibilities
- Data Pipeline Development: Build and maintain ELT (Extract, Load, Transform) processes to move data smoothly from source systems into Snowflake using tools like Snowpipe, Streams, and Tasks.
- SQL and Stored Procedures: Write advanced SQL queries, views, and stored procedures to clean, process, and analyze large volumes of data.
- Performance Tuning: Monitor query speeds, optimize resource use in virtual warehouses, and lower computing costs.
- Data Modeling: Design scalable database schemas, tables, and dimensional models tailored for business reporting.
- Security and Governance: Set up role-based access control (RBAC), data masking, and encryption to keep enterprise data safe and compliant.
- Data Migration: Move legacy databases and on-premises storage systems securely into the cloud environment.
Key Technical Skills
- Database Querying: Expert-level SQL and SnowSQL.
- Programming Languages: Python or Scala for automation and Snowpark development.
- Cloud & ETL Tools: Experience with cloud services (AWS, Azure, or GCP) and integration tools like dbt, Fivetran, or Informatica.
- Snowflake Features: Knowledge of Zero-Copy Cloning, Time Travel, and secure data sharing.
