About the Role:

Data is the driver for our future at Cars Commerce. We’re searching for a collaborative, analytical, and innovative engineer to build scalable and highly performant platforms, systems and tools to enable innovations with data. If you are passionate about building large scale systems and data driven products, we want to hear from you.

The Analytics Engineer within the Consumer Data Platform team focuses on enabling cars commerce to make informed and timely product decisions and also improve our marketing efficiencies and reach. The role sits at the intersection of software engineering, data engineering, and analytics (product and marketing) teams. You will be responsible for extracting, transforming, and integrating data and/or working with business partners. Utilizing analytics engineering tools and techniques , you will work in role that requires both the business acumen and contextual understanding of a data analyst and the technical skillset of a data engineer. You will be the subject matter expert of various datasets within the consumer domain.

Responsibilities Include:

• Codify the intent and context, implement data integrations and apply governance in the raw data to enable analytics and machine learning teams to build applications and drive insights.
• You will work with Product and Marketing to understand data applications and their relationship to business outcomes in depth. They will also work with other tech teams to develop and maintain the transformation layer using an engineering-first approach.
• You will also own the architecture of the integrations involved in CDP, rETL solutions and event generation systems. They will also maintain the documentation of business logic involved in transforming raw data.
• You will build assets that help improve trust in data (bot, ad-blocker logic) while also making data more accessible and explainable (helping teams understand u’sers’ intent behind activities).
• Be the resident expert in tag management.

Required Skills

• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, HiveQL, SparkSQL)
• Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
• Experience with any of ETL schedulers such as Airflow or similar frameworks.
• Experience with source code management systems such as Github and developing CI/CD pipelines with tools such as Jenkins, Github Action or CircleCI for data.
• Excellent communication and collaboration skills. 
• Ability to design, develop and debug at a cross-project level.
• Experience in the AWS (or any cloud services provider) environment and modern developer first data stacks like Rudderstack, Hightouch etc. 

Required Experience

• Data or Software Engineering | 3 years of designing & developing complex, real-time applications at enterprise scale; specifically Python and/or Scala. 
• Analytics Ecosystem | 2 years of hands-on, professional experience with analytical tools and platforms like Adobe, Amplitude or Google Analytics.
• AWS (preferred) Cloud | 2 years of professional experience.

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