Summer Data Engineering Intern

LPL Financial; Fort Mill (SC); On-site; USD 34,000 - 41,000; Full time

Job summary

LPL Financial offers a Data Engineering Intern role designed to help build and optimize data platforms supporting analytics, BI, and AI-driven decision making. You will collaborate with data engineering, analytics, and data product teams to develop pipelines, support reporting, and contribute to Generative AI initiatives.

This 10-week, 40-hour-per-week internship emphasizes data passion, technology, and solving business challenges to deliver client value.

Qualifications

• Pursuing a bachelor’s or master’s degree in Computer Science, MIS, Data Science, Analytics, Engineering, Mathematics, or a related field.
• Available to work from LPL Financial’s primary office locations.

Responsibilities

• Assist in building and maintaining data pipelines that ingest, process, and transform data from multiple sources.
• Support the development and optimization of data platforms, warehouses, lakes, and reporting solutions.
• Analyze, validate, and monitor data to ensure accuracy, quality, and reliability.
• Partner with data engineers, analysts, product managers, and business stakeholders to support analytics, reporting, and AI use cases.
• Contribute to the development of data products by gathering requirements, documenting business needs, and supporting product lifecycle activities.
• Leverage automation and AI-enabled tools to improve data workflows, operational efficiency, and insight generation.
• Assist with troubleshooting data pipeline issues, performance monitoring, and process optimization.
• Document data architectures, workflows, and technical specifications.

Job description

LPL Financial offers a Data Engineering Intern role designed to help build and optimize data platforms supporting analytics, BI, and AI-driven decision making. You will collaborate with data engineering, analytics, and data product teams to develop pipelines, support reporting, and contribute to Generative AI initiatives.

This 10-week, 40-hour-per-week internship emphasizes data passion, technology, and solving business challenges to deliver client value.