Senior AI & Data Engineer

What you'll do

• Architect and maintain a scalable Snowflake AI Data Cloud environment including compute optimization and cost management.
• Design and implement ELT/ETL frameworks using Snowpark Python, Dynamic Tables, Streams, Tasks, and Snowpipe.
• Build reusable, AI-ready data products with clear ownership, semantic context, and data quality SLAs.
• Implement enterprise security controls including RBAC/ABAC, dynamic data masking, and audit logging.
• Design and build multi-step agentic AI workflows using Snowflake Cortex AI functions and search.
• Develop production-grade Retrieval-Augmented Generation (RAG) pipelines with vector search and hybrid search capabilities.
• Define and enforce data modeling standards such as Kimball dimensional and Data Vault 2.0.
• Integrate Snowflake with upstream source systems, orchestration platforms like Airflow, and downstream analytics consumers.

What we're looking for

• Must have a minimum of three years of professional experience in data engineering, including building agentic AI or LLM-powered applications.
• Must have a minimum of three years of professional experience with Snowflake-native features like Snowpark, Dynamic Tables, and Cortex AI.
• Must have a minimum of three years of experience with Python for data engineering and ML workloads and advanced SQL.
• Must have a Bachelor's degree, or an Associate Degree with at least 6 years of work experience, or 12 years of work experience.
• Experience with data modelling methodologies and dbt for transformation layer management (preferred).
• Familiarity with at least one major cloud platform (AWS, Azure, or GCP) and associated services (preferred).
• Snowflake SnowPro Advanced certification or Cortex AI practitioner credentials (preferred).