Snowflake AI Data Engineer

Capgemini • New York, NY

2d • $72,000 - $101,050 • Onsite

About The Position

The Snowflake AI Data Engineer / Lead serves as the onsite technical lead, driving Snowflake-native AI, GenAI, and advanced data engineering on AWS Cloud. This role requires deep expertise in Snowflake, Cortex AI, Snowpark (Python), and Talend ETL, with ownership of delivering AI/ML and LLM-powered solutions directly within the Snowflake ecosystem, while coordinating with offshore teams.

Requirements

• Strong experience in Snowflake, Cortex AI, Snowpark (Python), Talend ETL, and AWS Cloud.
• Hands-on expertise in LLMs, embeddings, vector search, and RAG architectures within Snowflake.
• Proven leadership in Snowflake architecture, performance optimization, and scalable data platforms.
• Deep experience in data engineering, ELT pipelines, and real-time/batch data integration.
• Experience enabling AI/ML workloads and feature engineering within Snowflake environments.
• Strong knowledge of data security frameworks (RBAC, masking, row/column-level controls).
• Domain experience in insurance or financial services.
• Advanced proficiency in SQL and Python, with the ability to lead engineering teams.

Responsibilities

• Design and implement Cortex-driven AI solutions using LLM capabilities (COMPLETE, CHAT, SUMMARIZE), embeddings (EMBED_TEXT), vector search, and RAG architectures.
• Enable AI copilots, semantic search, and intelligent analytics on enterprise data.
• Own Snowflake platform architecture, including: Schemas, Views, Streams, Tasks, Snowpipes.
• Enforce performance optimization best practices: Warehouse sizing, Clustering, Query tuning.
• Implement secure data access using: RBAC, Masking, Row-level controls, Column-level controls.
• Lead data engineering and integration pipelines (batch and near real-time) using Talend, Qlik Replicate, and Snowpipe.
• Ensure data quality, reconciliation, and schema evolution.
• Enable ingestion from diverse source systems.
• Guide SQL, Python, and ELT transformations.
• Enable AI/ML workflows using Snowpark and integration with platforms such as: Databricks, SageMaker, Azure ML.
• Deliver AI-driven use cases such as: Claims triage, Fraud detection, Risk scoring, Premium leakage, Pricing analytics.
• Leverage Snowflake-native AI capabilities and Python-based data science frameworks.
• Support CI/CD-driven deployments and automation.

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed