Intern - Data Engineer

The Hanover Insurance Group•Worcester, MA
•$26 - $30

About The Position

The Hanover’s 10-week summer internship, running from June to mid-August, gives college students the opportunity to work on critical business assignments and apply their academic knowledge. Interns work on meaningful projects alongside industry talent and receive support and mentorship from leaders, managers, subject matter experts, and recent graduates. The program also includes a cross-functional corporate philanthropy project, weekly development workshops, and engagement and social activities. The company recruits skilled students for potential full-time employment after graduation. In this role, the intern learns where data resides, basic data models and architecture, how to access and obtain data, and how to manipulate data to produce reports, datasets, or self-service reports. The work focuses on practical applications of data collection and analysis, including data profiling, report and data generation, relational data modeling, data management and documentation, and implementing data pipelines and models. The intern documents the development and design of solutions.

Requirements

  • Currently enrolled in a bachelor's degree or advanced degree program.
  • Able to commit to a full-time, 10-week internship program.
  • Able to work in the U.S. without requiring sponsorship now or in the future.
  • Technical proficiency in ETL (such as Azure Data Factory or SSIS), SQL, data management, and documentation.
  • Demonstrates initiative, creativity, and analytical skills.
  • Thinks critically and anticipates, recognizes, identifies, and develops solutions.

Nice To Haves

  • Cumulative GPA of 3.0 or higher is preferred.

Responsibilities

  • Understand data locations, basic models and architecture, and how to access, obtain, manipulate, and work with data to produce reports, datasets, or self-service reports.
  • Apply data collection and analysis in practical settings.
  • Execute data profiling, report and data generation, relational data modeling design, data management, and documentation.
  • Implement data pipelines and models as needed for models or analysis.
  • Document the development and design of solutions.
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