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Data Preprocessing Engineer Intern

Marvell Technology·ישראל·en
במקום העבודהמשרה חלקיתData EngineeringSemiconductor Manufacturing

Hands-on internship for an advanced bachelor's student supporting AI research through semiconductor data collection, cleaning, transformation, and pipeline development.

תחומי אחריות

  • Collect, clean, normalize, and sanitize large-scale semiconductor chip design datasets
  • Build and maintain scripts and pipelines for automated data extraction and transformation
  • Parse JSON, CSV, Parquet, log, and domain-specific EDA files
  • Locate, understand, and extract relevant data from complex codebases and directory structures
  • Process structured and semi-structured data with SQL and Python
  • Collaborate with researchers and engineers to deliver model-ready datasets
  • Document data sources, transformation logic, and dataset versions

דרישות

  • Advanced bachelor's student in Computer Science, Software Engineering, Electrical Engineering, Data Science, or a related field
  • Strong Python skills, including hands-on pandas and NumPy experience
  • Solid SQL skills and experience with structured and semi-structured data
  • Practical experience cleaning, normalizing, and sanitizing real-world data
  • Ability to navigate codebases and file systems and parse multiple file formats
  • Git fluency, including reading commit history and diffs
  • Scripting skills for automating extraction and transformation tasks

יתרון

  • Exposure to Airflow, dbt, Spark, or similar data pipeline tools
  • Basic understanding of machine learning features and train/test leakage
  • Experience reverse-engineering undocumented data and identifying relationships across datasets

הטבות

  • Eligibility for bonus and equity plans, including a new-hire equity grant and annual equity refreshers
  • Competitive compensation and benefits
  • Collaborative, transparent, and inclusive work environment
  • Opportunities for learning and professional development

רלוונטיות

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משרות דומות

המשרות הפתוחות החדשות ביותר בתחום Data Engineering.

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