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Love your job.\nAs 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.\nSome of your responsibilities will include, but will not be limited to:\nAssisting in the development and maintenance of data pipelines and ETL/ELT workflows for processing datasets from multiple sources\nSupporting the building and optimization of data models, schemas, and databases to ensure efficient data storage and accessibility\nParticipating in data cleaning, validation, and quality checks to help deliver accurate and reliable data for analytical use\nWorking with SQL, Python, and modern data tools such as Spark to support data flows and data science initiatives\nCollaborating with data engineers and business teams to understand data requirements and contribute to solution development\nAssisting in monitoring data infrastructure performance and helping troubleshoot issues as needed\nContributing to documentation for pipelines, data models, and transformation logic\nLearning about emerging data technologies and supporting recommendations for data architecture improvements\nSupporting the implementation of software engineering best practices such as testing and monitoring in data workflows\nPut your talent to work with us as a Data Engineering Intern!\nTexas Instruments will not sponsor job applicants for visas or work authorization for this position.\n Minimum requirements:\nCurrently pursuing an undergraduate or graduate degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or related field\nCumulative 3.0/4.0 GPA or higher\nPreferred qualifications:\nCoursework or project experience with programming languages such as Python, Java, or SQL\nBasic understanding of database concepts and data manipulation\nExposure to big data platforms (e.g., Spark), cloud services (AWS, Azure, or GCP), or machine learning concepts 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