About The Position

This role is ideal for students who are interested in building the systems behind the data — transforming raw information into reliable, usable data assets that help teams make better decisions. As a Data Engineer Intern, you will help build and support the data pipelines, platforms, and processes that enable analytics, reporting, automation, and AI-driven insights across the organization. The Hartford’s Technology, Data, AI, and Operations organization offers an immersive summer internship program designed to help students explore career paths in technology, data engineering, cybersecurity, AI, analytics, data science, and technology operations within the insurance industry. As part of The Hartford’s growing investment in AI and advanced analytics, interns will explore how emerging technologies — including generative AI, machine learning, and automation — are transforming business operations, decision-making, and customer experience. In this role, you will gain hands-on experience supporting data solutions that help power business insights, analytics products, and future AI capabilities. This role is a hybrid position in Charlotte, NC. Candidates must be authorized to work in the US without company sponsorship now or in the future.

Requirements

  • Undergraduate or graduate student expecting to graduate in May 2028 with a Bachelor's or Master's degree and a GPA of 3.0 or higher
  • Pursuing a degree in Computer Science, Engineering, IT, Management Information Systems, Data Analytics, Applied Mathematics, or another STEM-related field
  • Strong analytical, problem-solving, and critical thinking skills
  • Strong communication, collaboration, and interpersonal skills
  • Curiosity and willingness to explore new technologies and challenge assumptions
  • Demonstrated ability to analyze complex problems using structured thinking and logical reasoning
  • Commitment to ethical judgment, responsible data use, and understanding how technology decisions affect stakeholders and the business
  • Experience and exposure to some or all of the following: Programming & Querying: Python, SQL, PL/SQL
  • Data Engineering: ETL/ELT, data pipelines, data transformation, data profiling, data quality, data modeling
  • Data Platforms & Tools: Snowflake, GitHub, relational databases, data warehouse concepts
  • Cloud Technologies: AWS, Azure, or Google Cloud
  • Analytics & BI: Tableau, dashboards, reporting, data mining, or business intelligence tools
  • AI & Emerging Technology: Familiarity with AI/ML concepts, generative AI tools, LLMs, NLP, or interest in building data foundations that support AI-driven solutions
  • Agile Ways of Working: Exposure to Agile teams, sprint delivery, or collaborative product-based work

Responsibilities

  • Build and support data pipelines that ingest, transform, and prepare data for business and analytical use
  • Work with structured and unstructured data to enable analytics, reporting, and AI-driven solutions
  • Apply data engineering tools and techniques (e.g., Python, SQL, ETL processes, cloud technologies) to develop reliable data assets
  • Ensure data quality, consistency, and performance through profiling, validation, and monitoring activities
  • Collaborate with cross-functional teams to deliver scalable data solutions that address business needs
  • Leverage AI tools (e.g., Copilot) to enhance productivity and support the development of data solutions that power advanced analytics and machine learning

Benefits

  • Mentorship, coaching, feedback, and self-directed learning opportunities
  • Networking, volunteerism, and employee engagement experiences with peers and leaders across the organization
  • A stronger understanding of how data supports decision-making within the insurance industry
  • Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition.
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