BayRockLabs - Data Engineer - Snowflake DB

<p><p><b>Description :</b></p><p><b><br/></b></p><p>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.<br/><br/>This role is crucial for ensuring the AI agents receive clean, aggregated, and optimized data efficiently.<br/><br/><b>Key Responsibilities :</b></p><p><b><br/></b></p><p>- 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.<br/><br/>- 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.<br/><br/>- ETL/ELT Development: Develop robust and performant ELT pipelines using Snowpipe, Tasks, Streams, and Dynamic Tables to aggregate data from diverse sources into Snowflake.<br/><br/>- 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.<br/><br/>- 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.<br/><br/>- Data Governance: Ensure data quality, lineage, and adherence to security policies (e.g., Row Access Policies, Data Masking) within the Snowflake environment.<br/><br/><b>Required Skills & Qualifications :</b></p><p><b><br/></b></p><p>- Expert-level proficiency in Snowflake architecture, optimization, and advanced features (e.g., Streams, Dynamic Tables, Time Travel).<br/><br/>- Deep expertise in SQL and data modeling for high-volume, complex datasets.<br/><br/>- Strong hands-on experience with Python and Snowpark for custom data transformation logic.<br/><br/>- Proven ability to perform data cleansing, feature engineering, and dimensional reduction (reducing columns).</p><br/></p> (ref:hirist.tech)