Gen AI Data Engineer — Remote, Snowflake & Cloud Pipelines

Sedgwick Claims Management Services Ltd; Tennessee; Hybrid; USD 140,000 - 210,000; Full time

Job summary

Sedgwick Claims Management Services Ltd is seeking an AI Engineer to architect and deliver enterprise data pipelines powering advanced analytics, ML, and generative AI initiatives. You will bridge legacy on‑prem systems with Snowflake and cloud ecosystems (AWS/Azure) while ensuring data quality, governance, and performance at scale.

The role is remote anywhere in the United States, requiring collaboration with IT, Data Science, and security teams to maintain robust data pipelines and governance

Qualifications

• Master’s degree in Computer Science, Data Engineering, or a related field preferred.
• Six years of hands-on data engineering experience building production-grade pipelines for Data Science/AI in multi-cloud environments.

Responsibilities

• Designs, builds, and maintains resilient ETL/ELT pipelines ingesting data from on-premise and cloud sources.
• Develops feature stores and datasets to support ML workflows.
• Engineers data pipelines for generative AI, including vectorization and embeddings across AWS/Azure.
• Acts as a Snowflake power user to optimize compute/storage for high-concurrency analytics.

Skills

Snowflake architecture

AWS & Azure data services

Python, SQL & PySpark

Data orchestration

Docker

Mainframe data integration

GenAI data workflows

Team collaboration

Performance optimization

Education

Master’s degree in Computer Science or Data Engineering

Tools

Snowflake

AWS

Azure

Python

SQL

PySpark

Docker

Job description

Sedgwick Claims Management Services Ltd is seeking an AI Engineer to architect and deliver enterprise data pipelines powering advanced analytics, ML, and generative AI initiatives. You will bridge legacy on‑prem systems with Snowflake and cloud ecosystems (AWS/Azure) while ensuring data quality, governance, and performance at scale.

The role is remote anywhere in the United States, requiring collaboration with IT, Data Science, and security teams to maintain robust data pipelines and governance