Data Engineer

Sedgwick is hiring a Data Engineer to build and support data pipelines for advanced analytics, machine learning, and generative AI work. The role is focused on creating production-ready data flows, connecting older on-site systems with cloud-based environments, and making sure data is prepared to meet technical and governance needs for model training and AI use. Day to day, the job involves designing, building, and maintaining ETL and ELT pipelines, as well as creating feature stores and curated datasets for data science teams. The advert names mainframe systems, SQL Server, DB2, Snowflake, AWS services such as S3 and RDS, and Azure tools including Blob Storage and Azure SQL. It also refers to work in AWS and Azure AI ecosystems and to data support for machine learning, inference, and retrieval-augmented generation use cases. The advert does not specify any required years of experience or a particular qualification. It also does not mention language requirements. The role is remote and full time. It appears aimed at someone who is comfortable building data foundations for analytics and AI initiatives in a hands-on engineering role.