Job Description
By joining Sedgwick , you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve. Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies Certified as a Great Place to Work® Fortune Best Workplaces in Financial Services & Insurance Data Engineer AI Role Overview As a Senior Data Engineer within the Transformation Office, you are the hands-on architect of the data supply chain for our most advanced initiatives. You will be responsible for the "heavy lifting" required to fuel Data Science models and AI applications with high-fidelity data. Your mission is to build the pipelines that bridge our legacy on-prem systems (Mainframes, SQL Server, DB2) with our modern Snowflake environment and AWS/Azure AI stacks. You are a "day-one" builder who ensures that data is not just moved, but engineered for the specific requirements of model training, feature stores, and RAG-based AI systems. Key Responsibilities Hybrid Data Pipeline Execution: Design and implement robust ETL/ELT pipelines to ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL), centralizing it for consumption in Snowflake and AI services. Engineering for Data Science: Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring Data Scientists have immediate access to clean, versioned, and statistically valid data. Engineering for AI (RAG & LLMs): Develop the data pipelines required for Generative AI, including the automated extraction, chunking, and loading of unstructured data into vector stores across AWS and Azure. Snowflake Power-User Execution: Act as the technical lead for our Snowflake data warehouse, implementing sophisticated data modeling, Snowpipe automation, and compute optim
