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Data Engineer Intern - Summer 2024

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CME Group

22d ago

🚀 Summer Internship


AI generated summary

  • You need SQL and Python skills, experience with big data tools like Hadoop, and familiarity with GCP cloud services. Actively enrolled in a graduate program in a quantitative field.
  • You will work on creating and optimizing data tools, building data pipelines, and developing analytics tools to provide insights into business performance metrics.

Summer Internship



  • CME Group is currently looking for a Data Science summer intern.
  • This candidate will assist the Data Science team on day-to-day activities in support of Data Engineering such as building python and bigquery based ETL applications, build bigquery SQLs to enhance business users experience with GCP datasets.


  • Skills / Software Requirements:
  • Working SQL knowledge and experience working with relational databases, NO-SQL, Columnar datastructures query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
  • Experience with Python programming language.
  • Having experience in any of the following software/tools is bonus:
  • Experience with big data tools: Hadoop, Spark, Kafka, etc.
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with data pipeline and workflow management tools: Argo, Airflow, etc.
  • Experience with GCP cloud services: Bigquery, Cloud Storage, GKE, Vertex AI Pipelines
  • Experience with DevOps technologies : Terraform, Jenkins
  • Education:
  • Actively enrolled in a Graduate program in Computer Science, Statistics, Data Engineer/ Data Science / Data Analytics, Informatics, Information Systems or another quantitative field.

Education requirements

Currently Studying

Area of Responsibilities



  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Create and maintain optimal data pipeline architecture,
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and GCP ‘big data’ technologies.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.


Work type

Full time

Work mode