Texas Instruments is looking to solve the problem of building and maintaining the data infrastructure and systems that power AI/ML, analytics, reporting, and data-driven decision-making across the organization by hiring a Data Engineer.
Requirements
- Proficiency in programming languages such as Python, Java, Scala, C/C++ and strong SQL skills for data manipulation and querying
- Understanding of ETL processes, database concepts, and experience with big data platforms (e.g., Spark), cloud services (AWS, Azure, or GCP)
- Experience with AI/ML frameworks (e.g., PyTorch) and large-scale data processing, including transformer-based LLMs and neural networks
- Knowledge of machine learning algorithms ranging from traditional ML to cutting-edge deep learning models
- Exposure to or proven experience in machine learning, deep learning concepts, NLP, computer vision, speech, and time series analysis
- Demonstrated ability to develop end-to-end data pipelines, AI-enabled data tools, or enterprise-scale data architecture solutions
Responsibilities
- Develop and maintain scalable data pipelines and ETL/ELT workflows for ingesting, processing, and transforming large datasets from multiple sources
- Build and optimize data models, schemas, and databases to ensure efficient data storage, accessibility, and performance
- Perform data cleaning, validation, and quality checks to deliver accurate and reliable data for analytical use
- Work with SQL, Python, and modern data tools such as Spark to automate data flows and support data science initiatives
- Architect and implement large-scale data engineering solutions across hybrid cloud environments
- Build reusable libraries and automated pipelines while applying software engineering best practices such as CI/CD, testing and monitoring
- Monitor data infrastructure performance and troubleshoot issues as needed
Other
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Data Science, or related field of study
- Cumulative 3.0/4.0 GPA or higher
- Strong analytical and problem-solving abilities with experience tackling complex, multifaceted challenges
- Proven teamwork and communication skills in multidisciplinary projects, including ability to present technical concepts to non-technical stakeholders
- Strong time management and project management skills that enable on-time delivery of high-impact projects
