Description

Lead end-to-end data architecture and solution design for Snowflake-based platforms, covering logical and physical data models, ingestion patterns, and consumption layers for analytics and AI.

This role is on-site.

Responsibilities

• Design scalable data warehouses, lakes, and lakehouse architectures on Snowflake, optimizing performance, cost, and workload strategies.
• Architect AI-powered solutions using Snowflake Cortex, including LLM functions, semantic search, and integration with external models.
• Define data governance, security, and compliance frameworks, including RBAC, dynamic data masking, and secure data sharing.
• Build real-time data pipelines using Streams, Tasks, Snowpark, and orchestration tools, integrating diverse on-prem and cloud sources.
• Lead migrations from legacy systems to Snowflake, establishing reference architectures and mentoring junior engineers.

Required Skills

• 8+ years in data architecture or engineering, with 4+ years specifically on Snowflake.
• Deep expertise in Snowflake features: warehouses, resource monitors, zero-copy cloning, Time Travel, Snowpark, and security controls.
• Strong SQL proficiency and experience with data modeling (conceptual, logical, physical) and ETL/ELT patterns.
• Experience with cloud data platforms (AWS, Azure, or GCP).
• Proven track record designing secure, scalable architectures for analytics and ML workloads.
• Solid understanding of data governance, quality, lineage, and compliance standards.
• Bachelor’s degree in Computer Science, Engineering, or related field.

Preferred Skills

• Hands-on experience with Snowflake Cortex AI capabilities (RAG, vector embeddings, LLM functions).
• Familiarity with modern data stack tools: dbt, Airflow, Kafka, Spark, or similar.
• Knowledge of Data Vault 2.0, dimensional modeling, or domain-driven design.

Key Skills

Education

Bachelor's degree