Senior Data Engineer, Predictive Modeling

Carvana
Tempe, AZPosted 7 March 2026

Job Description

<p><strong>About Carvana...</strong></p> <p>At Carvana, we’re changing the way people buy and sell cars. With an ambitious vision and a fundamentally different approach designed to be fun, fast, and fair, Carvana became the fastest-growing automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange, sold our 1 millionth car, and reached the Fortune 500, all in just eight years.</p> <p>Today, with 4 million retail customers and counting, Carvana is both the fastest-growing and the most profitable public automotive retailer, and we’re just getting started. We continue to raise the bar for our customers as we tackle the enormous opportunity still ahead in the largest consumer vertical.</p> <p>Working here means being part of a team that embraces change, celebrates creative problem solving, and always strives to be better. At Carvana, you’ll have the opportunity to take on meaningful challenges, learn quickly, and help shape the future of automotive retail. If you’re driven to grow and make an impact as part of a collaborative team, you’ll fit right in. Learn more about what it’s like to work here from the people that already do. </p> <p><strong>Work Model: </strong>This is a 100% on-site role at our Tempe office, Monday through Friday.</p> <p><strong>About the team and position</strong></p> <p>In today’s world, data is king and this is the team with all the data. If you’re excited about understanding complex data sets from disparate sources, this is the team for you. Our data science and analytics team automates everything Carvana does from modeling consumer behavior to understanding how to make our users’ lives better. </p> <p>Everyone wants to predict the future and this team does just that. We take data from across Carvana and external sources to understand past consumer behavior and how that can predict future behavior. Whether we’re looking at the credit risk of our consumers or just figuring out inventory and pricing strategies, this team is on top of it. </p> <p><strong>What you’ll be doing</strong></p> <ul> <li>Seek out, consume, and productionalize new data, both structured and unstructured, in support of our data science team.</li> <li>Design and maintain the predictive modeling data pipeline from data acquisition and facilitation of model building to production scoring and model maintenance.</li> <li>Architect robust and scalable data pipelines for predictive model training, monitoring, and serving.</li> <li>Support data scientists and software engineers in building and deploying new RESTful services.</li> <li>Design and develop high-availability applications using technologies like Docker and Kubernetes.</li> <li>Develop comprehensive solutions for application logging, error reporting, alerting, and task scheduling.</li> <li>Design both relational and non-relational data models for optimal storage and retrieval.</li> <li>Create ETLs to integrate data between different systems and formats using tools like Python, SQL Server Data Tools, etc.</li> <li>Design processes that contain sensitive data in a responsible manner (using certificates, hashing, AD permissions), ensuring that necessary security practices are followed.</li> <li>Have the ability to read beyond the initial specs of a project to determine if there is additional functionality that should be added.</li> <li>Use basic statistical and visualization techniques to analyze the resulting data sets of your processes.</li> <li>Learn and stay abreast of new technologies that can improve the efficacy of the analytics and data science teams. </li> <li>Excellent communication skills to explain technical concepts clearly</li> <li>Other duties as assigned.</li> </ul> <p><strong>What you should know</strong></p> <ul> <li>Bachelor of Science in Computer Science, Engineering, Applied Math, or Hard Sciences (Or equivalent practical experience). A graduate degree is heavily preferred.</li> <li>5+ years of experience in data engineering a ... (truncated, view full listing at source)
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