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Career Accelerator Program - Data Engineer

Texas Instruments
Richardson, USA
Mid
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Qualifications

  • Minimum Requirements:
  • Bachelor's degree in Electrical Engineering, Computer Engineering or related field of study
  • Minimum cumulative GPA 3.0/4.0
  • Preferred Qualifications:
  • Proficiency in at least one programming language commonly used in data engineering (Python, Java, or Scala)
  • Solid understanding of SQL and relational database concepts
  • Coursework or project experience involving data structures, algorithms, and software design fundamentals
  • Strong analytical and problem-solving skills, with the ability to learn new tools and technologies quickly in a fast-paced environment
  • Exposure to distributed data processing frameworks such as Apache Spark
  • Familiarity with streaming/event-driven architectures (e.g., Apache Kafka)
  • Understanding of modern data lake/lakehouse concepts, including table formats like Apache Iceberg and object storage systems (e.g., MinIO, S3)
  • Experience with SQL query engines for large-scale analytics (e.g., Trino/Presto)
  • Internship, co-op, academic research, or personal project experience involving big data pipelines, ETL/ELT workflows, or cloud/on-prem data infrastructure
  • Minimum Requirements: - Bachelor's degree in Electrical Engineering, Computer Engineering or related field of study - Minimum cumulative GPA 3.0/4.0 Preferred Qualifications: - Proficiency in at least one programming language commonly used in data engineering (Python, Java, or Scala) - Solid understanding of SQL and relational database concepts - Coursework or project experience involving data structures, algorithms, and software design fundamentals - Strong analytical and problem-solving skills, with the ability to learn new tools and technologies quickly in a fast-paced environment - Exposure to distributed data processing frameworks such as Apache Spark - Familiarity with streaming/event-driven architectures (e.g., Apache Kafka) - Understanding of modern data lake/lakehouse concepts, including table formats like Apache Iceberg and object storage systems (e.g., MinIO, S3) - Experience with SQL query engines for large-scale analytics (e.g., Trino/Presto) - Internship, co-op, academic research, or personal project experience involving big data pipelines, ETL/ELT workflows, or cloud/on-prem data infrastructure

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