Data Engineer, Predictive Modeling
Role details
Job location
Tech stack
Job description
We're not just building data pipelines; we're engineering intelligent systems that predict the future and automate complex decisions. This team takes data from across Carvana and external sources to understand past consumer behavior and predict future trends. Whether we're assessing credit risk, optimizing inventory and pricing strategies, or building AI agents that accelerate our analysts' productivity, we engineer solutions that directly impact millions of customers. As a Senior Data Engineer on this team, you'll help architect the technical foundation that makes our data science magic possible and scalable.
What you'll be doing
- Refactor and productionalize Python code from Data Scientists and Analysts, transforming experimental notebooks into reliable, maintainable, and production-ready applications with proper testing, error handling, and documentation.
- Design, architect, and maintain robust, scalable predictive modeling data pipelines across our data science ecosystem.
- Design, develop, and maintain internal tooling that accelerates productivity for our Analysts, Data Scientists, and Data Engineers.
- Support data scientists and software engineers in building and deploying new RESTful services.
- Apply software engineering best practices including code reviews, version control, testing frameworks, and continuous integration to ensure high-quality, maintainable codebases.
- Design and develop high-availability applications using technologies like Docker and Kubernetes with focus on scalability, reliability, and observability.
- Develop comprehensive solutions for application logging, error reporting, alerting, and task scheduling across distributed systems.
- Design both relational and non-relational data models for optimal storage and retrieval, considering performance, cost, and maintainability.
- Create robust ETL/ELT processes to integrate data between different systems and formats, ensuring data quality and lineage tracking.
- Design processes that contain sensitive data in a responsible manner (using certificates, hashing, AD permissions), ensuring that necessary security practices are followed.
- Read beyond initial project specifications to identify opportunities for improvement, additional functionality, and technical debt reduction.
- Collaborate with stakeholders to translate business requirements into scalable technical solutions.
- Mentor junior engineers and provide technical guidance on software engineering practices and data architecture decisions.
- Stay current with emerging technologies in data engineering, AI/ML tooling, and agentic workflows that can enhance team capabilities.
- Excellent communication skills to explain technical concepts clearly
- Other duties as assigned.
Requirements
-
Bachelor's degree in Computer Science, Engineering, Applied Math, or Hard Sciences, or similar field from an accredited undergraduate institution required.
-
5+ years of experience in data engineering and data warehousing.
-
2+ years of experience building production systems designed for scalability, availability, and robustness with emphasis on code quality and maintainability.
-
Strong software engineering fundamentals including object-oriented design, design patterns, testing methodologies, and code review practices.
-
Strong experience with at least one cloud service platform provider (AWS, Google Cloud Platform, Azure).
-
Strong coding and application development skills in Python.
-
Strong experience with enterprise software development using modern tools and approaches including:
-
Docker, Kubernetes, and container orchestration
-
Continuous Integration/Continuous Deployment (CI/CD) pipelines
-
Version control systems (Git) and collaborative development workflows
-
Code quality tools (linting, static analysis, dependency management)
Fluency in SQL and NoSQL databases with understanding of data modeling and optimization techniques.
Knowledge of API design, microservices architecture, and integration patterns for connecting AI agents with backend systems.
Familiarity with DevOps principles and CI/CD pipelines
Ability to independently manage and prioritize efforts and complete projects.
Experience with AI/ML tooling and agentic workflow development is a strong plus.
Strong communication skills with ability to explain technical concepts to both technical and non-technical stakeholders. The technical stack you'll be able to work with includes
-
Docker / Kubernetes
-
Cloud service platform providers (Google Cloud Platform, Azure)
-
Python
-
Flask
-
Object-oriented Programming
-
Data Science ecosystem (numpy, scikit-learn, Jupyter)
Snowflake
SQL Server and various database technologies
Apache Spark, DataBricks, * Must be able to read, write, speak and understand English.
Benefits & conditions
- Full-Time Salary Position with a competitive salary.
- Medical, Dental, and Vision benefits.
- 401K with company match.
- A multitude of perks including student loan payments, discounts on vehicles, benefits for your pets, and much more.
- A great wellness program to keep you healthy and happy both physically and mentally.
- Access to opportunities to expand your skill set and share your knowledge with others across the organization.
- A company culture of promotions from within, with a start-up atmosphere allowing for varied and rapid career development.
- A seat in one of the fastest-growing companies in the country.