Snowflake Data Engineer

Snowflake Data Engineer - focuses on designing, building, and optimizing cloud data warehousing solutions, ELT pipelines, and data architectures

Must Have Technical/Functional Skills

Data Pipeline Development: Build and maintain scalable ELT/ETL data workflows using SQL, Snowpark, and tools like dbt or Fivetran.

Snowflake Administration: Manage schema objects, virtual warehouses, clustering keys, micro-partitioning, and secure data sharing.

Performance & Cost Optimization: Monitor query performance, tune slow-running workloads, and control cloud compute costs.

Data Governance & Security: Implement role-based access control (RBAC), masking policies, and security compliance.

Collaboration: Partner with data analysts, data scientists, and business stakeholders to translate data requirements into optimized structures

Snowflake Schema, Database Extract Transform and Load (ETL), Data Management, SQL (Structured Query Language), Scalable System Development, Snowflake Schema, Information/Data Security (InfoSec), Warehousing, Data Partitioning, Cost Control, Core Technical Skills: Advanced SQL programming, data modeling (dimensional/star schema), and scripting in Python or Scala.

Snowflake Expertise: Hands-on experience with Snowpipe, Streams, Tasks, Stored Procedures, and Snowpark.

Cloud Platforms: Familiarity with cloud environments such as AWS, Microsoft Azure, or Google Cloud Platform.