We are seeking a highly skilled Snowflake Data Engineer to design, develop, and optimize our enterprise data foundation, specifically for our production-level AI applications built on Snowflake Cortex.

This role is crucial for ensuring the AI agents receive clean, aggregated, and optimized data efficiently.

Key Responsibilities :

- Snowflake Architecture & Design: Design and implement scalable and high-performance data models (e.g., Data Vault, Dimensional Modeling) within Snowflake, specifically structuring data for AI/ML consumption.

- Data Aggregation & Optimization: Lead the effort to reduce our existing columns down to the necessary, non-duplicated, and optimized feature set required by the AI Agents.

- ETL/ELT Development: Develop robust and performant ELT pipelines using Snowpipe, Tasks, Streams, and Dynamic Tables to aggregate data from diverse sources into Snowflake.

- Performance Tuning: Optimize Snowflake queries, clustering keys, and warehouse sizing to ensure low latency data retrieval for real-time agent workflows and baseline report generation.

- Collaboration: Work closely with the AI/ML Agent Developers to expose data via optimized views, UDFs, and Stored Procedures that can be easily called by Snowpark or Cortex Analyst tools.

- Data Governance: Ensure data quality, lineage, and adherence to security policies (e.g., Row Access Policies, Data Masking) within the Snowflake environment.

Required Skills & Qualifications :

- Expert-level proficiency in Snowflake architecture, optimization, and advanced features (e.g., Streams, Dynamic Tables, Time Travel).

- Deep expertise in SQL and data modeling for high-volume, complex datasets.

- Strong hands-on experience with Python and Snowpark for custom data transformation logic.

- Proven ability to perform data cleansing, feature engineering, and dimensional reduction (reducing columns).