Senior Data Engineer

“We believe CVNA is in the early stages of becoming the next U.S. retail category killer.” 

– Stephens Investment Bank, Analyst Report, Sept. 2024

Building leading-edge technology has been at the core of Carvana’s strategy since our founding, driving us to become the 3rd fastest company in history to organically reach the Fortune 500 following only Amazon and Google. Today, we remain founder-lead and as ambitious as ever. In 2024, we have not only emerged as the fastest growing automotive retailer, but also the most profitable thanks to our deep vertical integration across retail, lending, vehicle transportation, wholesale auctions, and more. 

If you want to grow not just as an Engineer but as a leader and business-builder, Carvana is the place for you. Our technology teams build: 

• End-to-end ecommerce for both selling and buying cars, including everything you see on Carvana.com and in our mobile apps.
• AI-driven customer support across chat, email, SMS, and voice, as well as a proprietary CRM platform to ensure the most efficient and highest quality customer experience.
• 360° vehicle photography and interactive merchandising using cutting edge computer vision and AI techniques.
• The most sophisticated and self-service automotive lending platform in the world.
• Systems and tools behind a nationwide logistics network that has delivered and picked up over 3 million cars via our fully owned and operated fleet of automotive haulers, efficiently managing distribution of our massive inventory to 85% of US driveways.
• Enterprise grade systems for operating the largest vehicle reconditioning facilities in the US, with workflow and automation to guide the work for everything mechanical, electrical, and cosmetic needed to bring each car to our high standards.
• Early adoption and customization of AI tools for optimizing our Developer efficiency and experience.

And much, much more…

THIS IS A 100% ON-SITE POSITION FROM OUR HQ IN TEMPE (Monday through Friday)

About the team and position

Join Carvana’s Verification Technology team as a Senior Data Engineer and take ownership of building and optimizing the data infrastructure that powers our operations. The Verification Technology team supports both customer-facing websites and internal tools used to review and approve vehicle orders prior to delivery.

In this role, you’ll collaborate closely with Engineering, Analytics, and Product Management to design scalable data architectures and pipelines that align with business needs. By crafting intuitive, well-structured data systems, you’ll empower analysts to surface actionable insights while ensuring seamless integration across teams. With a proactive mindset and a focus on delivering impactful solutions, you’ll play a key role in shaping Carvana’s data-driven future.

What you’ll be doing

• Use Snowflake to develop and maintain robust and scalable Enterprise-level data pipelines with SQL/NoSQL data wrangling.
• Leverage generative AI and intelligent coding assistants to accelerate development, optimize team workflows, and assist in troubleshooting.
• Move and shape structured and semi-structured data between various data platforms, including Snowflake, MS SQL Server (2022), Kafka, AWS S3, Azure DataLake, Azure Blob, Cosmo DB and Azure SQL DB
• Provide design feedback to software development teams, ensuring transactional data structures meet the requirements of downstream analytics
• Assist in the migration of legacy workloads/code from SQL Server to Snowflake, converting T-SQL and python to Snow SQL and Snowpark
• Assist with SQL and Snowflake performance troubleshooting and query tuning
• Plan project deadlines, coordinating with multiple teams and provide updates to leadership
• Utilize version control and deployment pipelines, preferably with Azure ADO with Git or GitHub and GitHub Actions
• Lead complex projects characterized by diverse scope and high complexity, requiring significant collaboration across multiple teams
• Lead team design sessions and code reviews
• Engaging with cross-functional project teams involving data scientists, product engineers, and analysts to achieve common