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Technology Intern - Data Engineering

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Charles Schwab Corporation
Full Time, Apprenticeship/Internship position
Listed on 2026-09-09
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 33000 - 47000 USD Yearly USD 33000.00 47000.00 YEAR
Job Description & How to Apply Below
Position: 2027 Technology Intern - Data Engineering

Your Opportunity

At Schwab, you're empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

Data Engineering Intern

Students interested in data engineering and analytics - apply to this role. Interns work alongside data professionals to support enterprise data platforms, data pipelines, data integration, and analytical solutions that drive business decisions. Participants gain exposure to designing scalable data solutions, data ingestion frameworks, and modern data engineering practices.

Data Engineering roles available in this track:

Data & Analytics

Data Scientist

Data Engineering / Business Intelligence

Data Protection & Attack Surface Management

AI Security

What you have

Required Qualifications

  • Currently enrolled in a bachelor's degree program and entering junior-level standing by internship start date.
  • Have not completed your bachelor's degree prior to the internship.
  • Able to commit to 40 hours per week during the 9-week Summer 2027 internship program.
  • Able to begin full-time employment between August 2027 and September 2028.
  • Authorized to work in the United States on a full-time basis without employer sponsorship.
  • Willing to relocate at personal expense if required.

Preferred Qualifications

  • Computer Science, Management Information Systems, or related discipline
  • Familiarity with programming concepts, databases, data science and data technologies
  • Interest in data analysis, data movement, ETL processes, and scalable data architecture

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