Data Engineer - Snowflake Context Supports design and build-out of Snowflake-based data pipelines and data marts, working within an established architecture to deliver scalable, well-tested data solutions across business domains.

Key Responsibilities
Build ingestion pipelines from source systems into Snowflake, following established schema and architecture design - Develop and maintain data transformation logic using SQL/dbt/Snowflake pipelines, based on defined business and technical requirements - Build and maintain aggregation and reporting layers feeding downstream dashboards and reporting tools - Implement data lineage and audit logging at the pipeline level to support traceability and compliance - Write and maintain automated tests, including data validation checks, to catch issues early and ensure pipeline reliability - Tune Snowflake objects for performance as data volumes and domain coverage grow - Support UAT activities and resolve defects, refine logic,



and iterate based on business and stakeholder feedback - Document pipelines and data objects to support maintainability and future extensibility

Required Skills Experience
Minimum 5 years of Data and Analytics Engineering experience - Strong SQL and Python - Hands-on experience with Snowflake Tasks, Streams, Energetic Tables, Snowpark - Snowflake Cortex (AI/ML functions within Snowflake) - dbt model development - Medallion architecture (bronze/silver/gold layering) for pipeline design - Experience building data pipelines and frameworks with solid data validation and testing practices - Robust pipeline/ELT engineering fundamentals - ingestion patterns, schema-on-write discipline, idempotent load design - Comfortable working within an established architecture and schema, executing to spec and maintaining best practices

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