Snowflake AI Data Engineer

Capgemini•New York, NY

1d•$103,330 - $128,656•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 ability to lead engineering teams

Responsibilities

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.
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.
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.
Supporting CI/CD-driven deployments and automation.

Benefits

Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits like adoption assistance, surrogacy, and cryopreservation
Social well-being benefits like subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs
Employee Resource Groups
Disaster Relief
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