Snowflake AI Data Engineer
About the Role
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
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.
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.
Qualifications
- 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.
Pay
The base compensation range for this role in the posted location is $72,000 to $101,050. Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The actual compensation offered may fall outside of the posted range and will be determined based on factors such as geographic location, education, certifications, relevant experience, skills, seniority, performance, market considerations, and internal pay equity.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Benefits
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits may include:
- 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