Data Engineer

Data Engineer designs, builds, and optimizes scalable data pipelines and architectures within the Snowflake cloud platform. Key responsibilities include creating ETL/ELT workflows (using tools like Airflow, dbt, Python), optimizing performance via clustering keys, implementing security (RBAC), and managing data integration to ensure high-quality data access for analytics. Pipeline Development: Develop and maintain efficient ELT/ETL pipelines using Snowflake SQL, Python, or Javascript. Data Modeling & Architecture: Design secure, scalable data models and schemas within Snowflake. Performance Optimization: Optimize Snowflake data warehouse performance, including warehouse sizing, caching, and clustering keys. Data Ingestion: Implement data ingestion using Snow pipe, Kafka, or ETL tools for various file formats (JSON, XML, CSV). Security & Compliance: Implement data security models, Role-Based Access Control (RBAC), masking policies, and data sharing capabilities. Automation: Create re-usable frameworks and automate data processes using Tasks and Streams.