Tech & Data Program Summer 2027 - Data Engineer Intern (Chicago)
The Hartford · Chicago, IL · 2 days ago
On-siteInformation TechnologyFull-time
Student Intern - HHSIAN We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. 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. About The Experience 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 Chicago, IL. Candidates must be authorized to work in the US without company sponsorship now or in the future. What You'll Gain Hands-on experience designing, building, and supporting data pipelines and data workflowsExposure to modern data engineering practices, including ETL/ELT, data transformation, data quality, and cloud-based data platformsOpportunities to work with tools and technologies such as Python, SQL, PL/SQL, Snowflake, GitHub, and cloud platformsExposure to how data engineering enables analytics, reporting, automation, machine learning, and AI use casesMentorship, coaching, feedback, and self-directed learning opportunitiesNetworking, volunteerism, and employee engagement experiences with peers and leaders across the organizationA stronger understanding of how data supports decision-making within the insurance industry Ways You'll Learn, Grow, and Contribute Depending on your role and project assignments, your experience may include: Build and support data pipelines that ingest, transform, and prepare data for business and analytical useWork with structured and unstructured data to enable analytics, reporting, and AI-driven solutionsApply data engineering tools and techniques (e.g., Python, SQL, ETL processes, cloud technologies) to develop reliable data assetsEnsure data quality, consistency, and performance through profiling, validation, and monitoring activitiesCollaborate with cross-functional teams to deliver scalable data solutions that address business needsLeverage AI tools (e.g., Copilot) to enhance productivity and support the development of data solutions that power advanced analytics and machine learning Required Qualifications 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 higherPursuing a degree in Computer Science, Engineering, IT, Management Information Systems, Data Analytics, Applied Mathematics, or another STEM-related fieldStrong analytical, problem-solving, and critical thinking skillsStrong communication, collaboration, and interpersonal skillsCuriosity and willingness to explore new technologies and challenge assumptionsDemonstrated ability to analyze complex problems using structured thinking and logical reasoningCommitment 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/SQLData Engineering: ETL/ELT, data pipelines, data transformation, data profiling, data quality, data modelingData Platforms & Tools: Snowflake, GitHub, relational databases, data warehouse conceptsCloud Technologies: AWS, Azure, or Google CloudAnalytics & BI: Tableau, dashboards, reporting, data mining, or business intelligence toolsAI & Emerging Technology: Familiarity with AI/ML concepts, generative AI tools, LLMs, NLP, or interest in building data foundations that support AI-driven solutionsAgile Ways of Working: Exposure to Agile teams, sprint delivery, or collaborative product-based work Our internship program is designed as a pipeline for future full-time opportunities. High-performing interns may be considered for full-time roles within The Hartford’s Technology & Data organization. Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age