Data Engineering Intern – Platform & Product

Artisan PartnersMilwaukee, WI
Hybrid

About The Position

We are seeking a curious and motivated Data Engineering Intern to join our growing Data Engineering function. In this hands-on role, you’ll work alongside experienced engineers, architects, and analysts to build and test real data pipelines on our Snowflake-based cloud data platform. You’ll gain experience across the data engineering lifecycle, from sourcing and transforming data to testing, documenting, and delivering trusted datasets that support analytics and AI across the firm. The ideal candidate is a current undergraduate student with foundational programming and database skills who is eager to learn how enterprise data platforms are designed, built, and operated. Mentorship, code review, and regular feedback are built into the internship.

Requirements

  • Currently pursuing an undergraduate degree with demonstrated academic achievement.
  • Foundational SQL skills — comfortable writing queries with joins, filters, and aggregations
  • Some programming experience in Python or a similar language; coursework, personal projects, and prior internships all count
  • Familiarity with basic data concepts such as tables, relationships, and common file formats (CSV, JSON)
  • Clear written and verbal communication, a collaborative attitude, and a willingness to ask questions

Nice To Haves

  • Exposure to cloud platforms, Git, or dbt is a plus but not expected
  • Interest in financial or investment data (trading, pricing, benchmarks) is a plus; industry experience is not required

Responsibilities

  • Help build and test data pipelines that source, transform, and deliver datasets into Snowflake
  • Write and tune SQL to explore data, validate results, and support data quality checks
  • Contribute to platform tooling such as AI semantic layers, validation utilities, and reusable pipeline components
  • Leverage AI tooling to create user experiences in our data platform
  • Participate in the team’s regular routines, including sprint planning, stand-ups, and code reviews
  • Document what you build, including pipeline logic, data definitions, and how-to guides for the team
  • Scope and complete an end-of-internship project, and present the results to the Data Services team
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