AI/ML Engineer – R01570580

Primary Skills

• DataStream, ETL Fundamentals, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Time Travel and Fail Safe, Snowpipe, SnowSQL, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL, Stored Procedures

Job requirements

• Role Overview We are looking for a Snowflake Cortex + SQL Developer with strong SQL fundamentals and an interest in Generative AI. The candidate will work on Snowflake data solutions and leverage Snowflake Cortex AI Functions to build AI-powered data processing and analytics use cases. Key Responsibilities Develop complex SQL queries, joins, CTEs, views, stored procedures and data transformations in Snowflake. Work with Snowflake Cortex AI Functions such as AI_COMPLETE, AI_CLASSIFY, AI_EXTRACT, AI_SENTIMENT, AI_EMBED and AI_SUMMARIZE_AGG. Build AI-powered data processing and analytics solutions using SQL. Work with structured and unstructured data within Snowflake. Perform data validation, quality checks and troubleshooting. Optimize SQL queries for performance and cost. Support development of GenAI use cases such as summarization, classification, information extraction and semantic search. Collaborate with data engineers, analysts and business teams to understand requirements and deliver solutions. Required Skills Strong knowledge of SQL. Good understanding of Snowflake concepts and data warehousing. Basic understanding of Generative AI / LLM concepts. Hands-on or academic exposure to Snowflake Cortex / Cortex AI Functions. Knowledge of data transformation, joins, CTEs and analytical functions. Good problem-solving and analytical skills. Education Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.

Responsibilities

• Lead end-to-end execution of projects and cross-functional deliverables for AI/ML Engineer - R01570580.
• Collaborate closely with departmental peers and stakeholders to ensure seamless operational continuity.
• Monitor core performance KPIs, troubleshoot bottlenecks, and implement optimization protocols.
• Champion high quality standards, peer reviews, and comprehensive team documentation.