Data Engineer Intern

Data Engineer Intern – Summer Intern 2026

The Company

Munich Re America Services (MRAS) is a shared service organization that delivers services to all Munich Re US P&C Companies and other group entities.

The Opportunity

The Data Engineer Intern will gain hands-on experience with enterprise data engineering tools and practices at scale. Working with Databricks and Azure Data Factory teaches cloud-based data processing using Python and Spark SQL. Daily responsibilities in data matching, transformation, and pipeline development build both technical depth in data engineering and practical SQL and Python skills. The intern will learn best practices for building reliable, maintainable data systems; managing real ADF pipelines and handling data from multiple sources develops problem-solving abilities in a high-stakes environment where data quality directly impacts business outcomes.

We are seeking a strong candidate with foundational understanding of data engineering principles and cloud platforms. Success in this role requires comfort working with large datasets, attention to detail in data matching and validation, and ability to troubleshoot complex pipelines. Experience with SQL and Python is essential. This is a hands-on role where interns will own pieces of production pipelines and see their work directly impact data quality and business analytics.

Responsibilities:

• Load and ingest data from multiple sources into Databricks using Azure Data Factory (ADF) pipelines
• Write Python and Spark SQL code in Databricks Notebooks to transform and process large datasets
• Perform data matching and reconciliation across various data sources
• Execute data aggregation and calculations to prepare datasets for analysis
• Design and optimize ADF pipelines for reliability and performance
• Monitor and troubleshoot ADF pipelines and Databricks jobs
• Document data workflows, transformation logic, and pipeline architecture
• Collaborate with data analysts and stakeholders to understand requirements and validate outputs

Job Requirements:

• Grade Level: Rising juniors (2028) and seniors (2027); master’s students will not be considered
• Preferred major: Data & Information Science, Statistics and Machine Learning
• Communication and clarity in writing and verbal explanations
• Collaboration and teamwork
• Problem-solving and critical thinking
• Attention to detail
• Time management and ability to prioritize tasks
• Adaptability and willingness to learn
• Taking initiative and ownership of work
• Receiving feedback and implementing improvements
• Asking clarifying questions when needed

• Documentation and knowledge sharing
• Computer Skills:
  • Python
  • SQL
  • Apache Spark and Spark SQL
  • Databricks
  • Azure Data Factory (ADF)
  • Azure or AWS Experience preferred
  • Git and version control
    • Testing & Debugging

• Other Skills:
  • Technical documentation and knowledge sharing
  • Research and information gathering
  • Data pipeline understanding
  • Understanding of data governance and security best practices
  • Basic data quality and validation awareness
  • Open course and contribution experience

This role will be based in Princeton, NJ. The base range for this internship will be $21.00 - $22.00 per hour. Factors that may be used to determine your actual rate will include your specific skills, level of schooling and how many years of experience.

At Munich Re, we see Diversity, Equity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.