United States /
R&D – Engineering /
RevolutionParts is dedicated to modernizing the auto industry through our parts e-commerce platform. And we are pretty great at it too! We have enabled thousands of dealerships to sell auto parts online by transforming the way buyers and sellers connect.
And not only are we dedicated to revolutionizing the auto industry; we are also passionate about building a revolutionary team. Our Revolutionaries (as we call ourselves) are talented humans who have a shared goal of delivering an exceptional product and customer experience. Plus, we have fun while doing it!
RevolutionParts is on a mission to take our data to the next level. In this key role, you will help design and implement the next generation of our ETL pipeline for our parts catalog, pricing, and inventory data, which powers all of our eCommerce solutions. You will also be involved in establishing an enterprise-grade data platform for our largest partners. This is a high-impact role where you will be driving initiatives affecting teams and decisions across the company and setting standards for all our data stakeholders. Does the idea of spearheading a data practice in a high-growth e-commerce business sound exciting? If so, read on.
- We’re pulling in diverse data sources. You’ll need to learn our data and bring a strong grasp of ETL & ELT, workflows, AWS Glue, and data organization via efficient data lake and relational designs.
- You will help design and build all stages of data from access to transformation and modeling.
- You will build quality into the pipeline from day one using automated tests and data validation.
- You will work with stakeholders in Product and data science to run ad hoc analysis of our data to answer questions and help prototype solutions.
- You must own business problems through to resolution both individually and as part of a data team.
- You will support product engineering teams by performing query analysis and optimization, as well as work with product teams to implement data driven product features.
- You should have 4+ years experience as a data engineer; or at least 2 years experience as a Data Engineer and 3+ as a software engineer.
- You need to show us that you know what good looks like. This means experience implementing automated tests in a multi-stage data pipeline to ensure quality.
- You are highly analytical and curious by nature.
- You must have the ability to own business problems and the design and solutions that drive business outcomes.
- You must be a team player with the ability to work with others and know when to support and when to push.
- This role requires strong communication and collaboration skills; comfortable discussing projects with anyone from end users up to executive leadership.
- Fluency with the programming language of your trade. Our primary languages for data are Golang and Python, but we use others as well. You must be comfortable learning new skills on the job.
- We require fluency with best practices in an object-oriented design and programming; experience as a backend software engineer is necessary. Demonstrable experience with a functional paradigm is also valuable.
- The ability to write and optimize complex SQL statements is a base requirement.
- Familiarity with ETL/ELT pipelines and modern tools is fundamental to this role. We are building workflows managed in Argo utilizing Docker containers deployed within Kubernetes.
- You should have experience working in a cloud-based software development environment, preferably with AWS.
- Familiarity with no-SQL databases such as ElasticSearch, DynamoDB or others is helpful.
- Bachelor’s Degree in Computer Science or equivalent is required.
RevolutionParts is proud to provide all full-time Revolutionaries with a comprehensive employment package including competitive compensation, career development, benefits, 401K match, parental leave, and many more valuable perks. You can learn more about our core-value driven culture at our career page.
RevolutionParts is an Equal Opportunity Employer; we value diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, gender orientation, gender identity or expression, sexual identity, sexual orientation, age, marital status, family status, genetic information, veteran status, or disability status.