Information Technology Intern – Data Engineering

As a Data Engineering intern, you'll help build the data infrastructure that powers TI's AI/ML initiatives, analytics, and data-driven decision-making across the organization. You'll work with cutting-edge data technologies and cloud platforms, gaining hands-on experience in transforming raw data into actionable insights. And, you'll have the opportunity to work in exciting areas like machine learning pipelines, big data processing, AI-driven analytics, cloud data architecture, real-time data streaming, and automated data workflows.

• →Assisting in the development and maintenance of data pipelines and ETL/ELT workflows for processing datasets from multiple sources
• →Supporting the building and optimization of data models, schemas, and databases to ensure efficient data storage and accessibility
• →Participating in data cleaning, validation, and quality checks to help deliver accurate and reliable data for analytical use
• →Working with SQL, Python, and modern data tools such as Spark to support data flows and data science initiatives
• →Collaborating with data engineers and business teams to understand data requirements and contribute to solution development
• →Assisting in monitoring data infrastructure performance and helping troubleshoot issues as needed
• →Contributing to documentation for pipelines, data models, and transformation logic
• →Learning about emerging data technologies and supporting recommendations for data architecture improvements
• →Supporting the implementation of software engineering best practices such as testing and monitoring in data workflows

Put your talent to work with us as a Data Engineering Intern!

Texas Instruments will not sponsor job applicants for visas or work authorization for this position.

• Currently pursuing an undergraduate or graduate degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or related field
• Cumulative 3.0/4.0 GPA or higher

• Coursework or project experience with programming languages such as Python, Java, or SQL
• Basic understanding of database concepts and data manipulation
• Exposure to big data platforms (e.g., Spark), cloud services (AWS, Azure, or GCP), or machine learning concepts through coursework or personal projects
• Ability to establish strong relationships with key stakeholders critical to success, both internally and externally
• Strong verbal and written communication skills
• Ability to quickly ramp on new systems and processes
• Demonstrated strong interpersonal, analytical and problem-solving skills
• Ability to work in teams and collaborate effectively with people in different functions
• Ability to take the initiative and drive for results
• Strong time management skills that enable on-time project delivery