Tech & Data Program Summer – Data Engineer Intern; Hartford

Tech & Data Program Summer 2027 – Data Engineer Intern Program Overview

At The Hartford, we foster an inclusive and collaborative environment where every voice is valued and every idea can make an impact. Our culture is built on integrity, innovation, and a customer‑first mindset. We believe in empowering employees to grow through continuous learning, mentorship, meaningful work, and opportunities to contribute to solutions that support our customers and business. 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.

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. Bring your curiosity, technical mindset, and willingness to learn. Your voice and perspective matter here.

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 Hartford, CT. Candidates must be authorized to work in the US without company sponsorship now or in the future.

• Hands‑on experience designing, building, and supporting data pipelines and data workflows
• Exposure to modern data engineering practices, including ETL/ELT, data transformation, data quality, and cloud‑based data platforms
• Opportunities to work with tools and technologies such as Python, SQL, PL/SQL, Snowflake, Git Hub, and cloud platforms
• Exposure to how data engineering enables analytics, reporting, automation, machine learning, and AI use cases
• 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

• 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

• 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, Git Hub, relational databases, data warehouse concepts
• Cloud Technologies: AWS, Azure, or Google Cloud
• Analytics & BI:
  Tableau, dashboards, reporting, data…