Data and Analytics Intern

Arch Insurance Group Inc.
Farmington, Connecticut, United StatesPosted Aug 31, 2026

About the role

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠. About This Internship Arch’s internship program offers students a unique opportunity to gain hands on experience in the insurance industry. It provides challenging learning experiences that serve as a foundation for interns to explore their career choices and to develop professional skills. Working alongside some of the most talented members of the specialty insurance industry, interns will gain relevant expertise in various aspects of the field, participate in learning activities and receive ongoing feedback. About This Role Collaborate with the Data and Analytics team and business partners on projects that support critical business priorities. Design ETL processes, develop data pipelines, and support the implementation of validation controls to help ensure data accuracy and reliability. Integrate data from source systems, databases, APIs, and third-party applications into the segment data warehouse based on business needs. Support data quality activities by applying validation, profiling, and cleansing techniques to help ensure data is accurate, complete, and fit for business use. Design and develop Power BI reports and dashboards that provide meaningful insights into business operations. Troubleshoot and help resolve issues related to data sources, ETL processes, data pipelines, and data storage. Stay current with emerging technologies, trends, and best practices in data warehousing, analytics, cloud platforms, and responsible AI-assisted development. Explore and apply AI-enabled tools to improve productivity, automate repeatable tasks, support data quality analysis, and accelerate insight generation. Recommend improvements to existing data warehouse and analytics solut

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