Opening For Data Engineer - Snowflake

Key Responsibilities

• Pipeline Development: Build, monitor, and maintain scalable data ingestion and transformation pipelines using Python and Snowflake.
• Data Warehousing: Design and manage optimized data models, schemas, and warehouse architecture within Snowflake.
• Query Optimization: Write and tune complex SQL queries, window functions, and Common Table Expressions (CTEs) for maximum performance.
• Feature Exploitation: Implement native Snowflake features like Snowpipe, Tasks, Streams, Stored Procedures, and Snowpark.
• Data Integration: Connect to REST/SOAP APIs, cloud storage, and relational databases to extract and normalize diverse file formats (JSON, CSV, Parquet).
• Quality Assurance: Develop validation and automated testing frameworks to enforce data reliability, governance, and error handling.
• Collaboration: Work closely with Data Analysts, Scientists, and Product Teams to translate complex business objectives into production-ready pipelines.

Mandatory Technical Skills

• Snowflake: Expert-level knowledge of architecture (compute vs. storage separation), micro-partitioning, and performance tuning.
• Python: Strong programming proficiency for data manipulation, file parsing, and system automation.
• SQL: Mastery of advanced relational database querying, optimization strategies, and analytical indexing.
• Data Modeling: Solid understanding of dimensional modeling, Star/Snowflake schemas, and Fact/Dimension configurations.