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# Snowflake AI Data Engineer

- **Company:** Capgemini
- **Location:** Bridgewater, NJ, United States
- **Salary:** $103,330.0 - $128,656.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, ARM Architecture, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Security, Fraud Prevention and Detection, Python (Programming Language), Performance Tuning, Query Optimization, Role-Based Access Control, Azure Machine Learning, Search Technologies, SQL Databases, Talend, Enterprise Data Management, Feature Engineering, Large Language Models, Snowflake, Qlikview, Data Management, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** August 13, 2026
- **Apply:** https://www.careerjet.com/job/us2279272ba346e64bb4b57d069e2ab4a0/eaa

## About the Role

* 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 ability to lead engineering teams

## Description

* 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., * Designing and implementing Cortex-driven AI solutions using LLM capabilities (COMPLETE, CHAT, SUMMARIZE), embeddings (EMBED_TEXT), vector search, and RAG architectures, enabling AI copilots, semantic search, and intelligent analytics on enterprise data. Ownership of Snowflake platform architecture (schemas, views, streams, tasks, Snowpipes) is required, along with enforcing performance optimization best practices (warehouse sizing, clustering, query tuning) and implementing secure data access using RBAC, masking, and row/column-level controls.
 * The role includes leading data engineering and integration pipelines (batch and near real-time) using Talend, Qlik Replicate, and Snowpipe, ensuring data quality, reconciliation, and schema evolution, and enabling ingestion from diverse source systems. Guiding SQL, Python, and ELT transformations, and enabling AI/ML workflows using Snowpark and integration with platforms such as Databricks, SageMaker, and Azure ML.
 * Additional responsibilities include delivering AI-driven use cases such as claims triage, fraud detection, risk scoring, premium leakage, and pricing analytics, leveraging Snowflake-native AI capabilities and Python-based data science frameworks, and supporting CI/CD-driven deployments and automation.


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