Data Engineering Intern

Buildertrend Solutions•Omaha, NE

6d•Onsite

About The Position

As a Data Engineering Intern, you'll spend the summer building the datasets and pipelines that teams across Buildertrend rely on to make decisions. You'll work alongside experienced data engineers, get hands-on with a modern data stack, and learn how raw data from tools like Salesforce and SQL Server becomes curated, trustworthy datasets that power our BI, analytics and AI initiatives. We don't expect you to already know every framework we use. We're looking for curiosity, solid fundamentals and a real interest in the craft of data engineering. By the end of the internship, you'll have sharpened your technical skills, gained real engineering experience and shipped work that helps the business run on numbers people can trust.

Requirements

Currently pursuing a bachelor’s degree in computer science, data science, or a related field.
Available to work full-time onsite at the Buildertrend HQ in Omaha, NE, for the full summer.
Strong interest in data engineering, including building datasets, ETL/ELT, and getting data ready to support BI, analytics and ML/AI work.
Familiar with SQL and at least one programming language such as Python (through coursework or personal projects is perfectly fine).
Curiosity about data tools and frameworks like Databricks and dbt, and an eagerness to learn them on the job.
Experience using AI tools (such as Claude, GitHub Copilot or similar) in coursework or personal projects, or a strong interest in learning how to use them effectively.
Strong problem-solving and analytical skills, and comfort working with data.
Clear and effective written and verbal communication skills.
Comfortable working independently and as part of a team.
Eager to learn, ask questions and apply feedback constructively.

Responsibilities

Help build and maintain ELT/ETL pipelines that bring data in from sources like SQL Server, Salesforce and other business tools, and turn it into clean, usable datasets.
Write SQL to transform, model and prepare data that supports BI, product analytics, and ML/AI use cases.
Partner with Data Engineers, Analysts and other stakeholders to understand what a dataset needs to do before you build it.
Learn our modern data stack, including Databricks, dbt and a medallion (bronze, silver, gold) approach to organizing data, with guidance and mentorship along the way.
Write and run data quality and freshness checks so the teams using your datasets can trust the numbers.
Document what you build, including table definitions, column notes and simple diagrams, clearly enough for both people and AI tools to use.
Use AI-assisted development tools, including Claude, to accelerate coding, debugging and problem-solving workflows while still being responsible and accountable for the quality and accuracy of your work.
Complete assigned tasks and projects within established sprint timelines.