At Carvana, we sell cars, but we’re not salespeople. Since 2013, we’ve been making it our mission to change the way people buy cars. We saw a huge problem with how much it can suck to buy a car the traditional way, so we committed ourselves to tackling one of the largest, yet-to-be-disrupted markets in the world – the $1T per year U.S. car market (yes, that’s $Trillion with a “T”).
With the ability to search thousands of vehicles from our expansive inventory, to high-resolution 360° photographs of our vehicles’ interior and exterior, to real-time financing and the ability to complete contracts without visiting the back room of a dealership, we provide a seamless, online car buying experience for consumers that can be completed from their desktop or mobile device. All our vehicles are inspected and reconditioned based on our 150-point certification checklist and come with a 7-day return policy. We also operate our own logistics network to deliver cars to customers as soon as the next day, as well as offer customer pick-up at our state-of-the-art Car Vending Machine locations (yes, you read that right). By putting customer satisfaction at the core of our business, we’ve built a no-pressure, no-haggle online car buying experience that our customers time and money.
For more information on Carvana and our mission, sneak a peek at our company introduction video.
We are looking for a Data Engineer to support our Finance team. The successful candidate will work with our data science and business intelligence teams to seek out, consume and productionalize new data, both structured and unstructured. Additionally, you will be responsible for designing and maintaining the predictive modeling data pipeline from data acquisition and facilitation of model building to production scoring and model maintenance. The candidate will thrive in a fast-paced, challenging environment and be comfortable managing multiple disparate projects and using myriad tools such as Spark, MS SQL, Python, R, etc. as necessary to get the job done. You will have an insatiable curiosity and drive to learn and implement new technologies, programming languages and database systems to help ensure you and our Data Scientists are maximizing business impact.
As a Data Engineer in Data Science you can expect to…
- Work with data scientists to support model building, scoring, monitoring, and reporting.
- Identify, collect, store, process and analyze data using various storage engines (MS SQL Server, Spark, etc.)
- Design how data is stored, consumed, integrated, and managed
- Be focused on choosing optimal solutions to use for those purposes, and then implement, maintain, and administer them
- Design large relational data sets from unstructured data
- Create data flows to automate the use of algorithms created by our data scientists
- Plan, design, and optimize data processes and structures for throughput and query performance
- Ensure the accuracy and integrity of the data sets before they are presented to end users
- Create ETLs to integrate data between different systems and formats using tools like python, SQL Server Data Tools, etc.
- Design processes that contain sensitive data in a responsible manner (using certificates, hashing, AD permissions), ensuring that necessary security practices are followed
- Have the ability to read beyond the initial specs of a project to determine if there is additional functionality that should be added
- Use basic statistical and visualization techniques to analyze the resulting data sets of your processes
- Learn and stay abreast of new technologies that can improve the efficacy of the analytics and data science teams
- Quantitative undergraduate degree (such as math, economics, statistics, engineering, etc.) with a strong academic record, graduate degree preferred
- Minimum 3 years of professional experience in analytics, engineering, or data science
- You are well-versed in SQL and Python, or a similar language that will easily transfer to Python such as Java or C++
- Experience with a cloud platform such as AWS, Azure, or similar
- Experience with CI/CD pipelines such as Jenkins, Azure DevOps (VSTS), or similar
- You hold (or have the equivalent experience to) a degree in a technical or quantitative field, such as Computer Science, Information Systems, Engineering, Statistics, Applied Mathematics, etc.
- You have extensive knowledge of ETL processing – data manipulation, database structure, and data management.
- You follow software engineering best practices using tools such as unit testing and git
- You are a self-starter with the ability to lead and build trust quickly
- You have strong diagnostic and analytical skills, along with the ability to breakdown complex, cross-functional business problems
- Have a deep love for data, an analytical brain, and some serious technical aptitude
- You are fearless of being un-knowledgeable about a particular subject area/technology; you yearn to learn and ask questions, with a strong desire to grow through challenging work and new technologies
NICE TO HAVES:
- Exposure to a big data platform, such as Hadoop and AWS
- Experience with a data visualization tool
- Knowledge of a statistics package such as R, SAS, or pandas in Python
- Experience deploying Docker containers to production
What you can expect in return….
- A full-time, salaried position
- Medical (employee medical fully paid by Carvana), Dental, and Vision benefits
- A 401K with company match
- All the snacks and drinks your heart desires (plus iced coffee on tap!)
- Access to opportunities to expand your skill set and share your knowledge with others across the organization
Carvana is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
This role is not eligible for visa sponsorship.