Engineer II, Data

About the role

The bulk of the data engineer’s work would be in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers (like business/data analysts, data scientists or any persona that needs curated data for operational and analytical data use cases. Data engineers also need to guarantee compliance with data governance and data security requirements while creating, improving and operationalizing these integrated and reusable data pipelines. This would enable faster data access, integrated data reuse and vastly improved time-to-solution for CarMax’s operational and analytical initiatives.

Responsibilities

• Design, build, and maintain production-grade data pipelines (streaming and batch)
• Implement event-driven ingestion and near real-time processing
• Build transformations using distributed data processing frameworks
• Write and maintain clean, testable Python code following software engineering best practices
• Support CI/CD pipelines, automated deployments, and environment promotions
• Monitor and troubleshoot pipeline failures, latency issues, and data quality problems
• Collaborate closely with Data Scientists, Analysts, and platform engineers

Requirements

• 2+ years of experience as a Data Engineer or Software Engineer working with data
• Strong experience writing production Python code
• Experience building and supporting pipelines on Azure or an equivalent cloud platform (AWS/GCP)
• Hands-on experience with distributed data processing, such as: Apache Spark, Databricks (or Spark runners such as EMR, Dataproc)
• Experience working with event streaming or messaging platforms, such as: Azure Event Hubs, Apache Kafka / Confluent Kafka, Amazon Kinesis
• Practical experience with CI/CD pipelines, version control, and automated deployments
• Familiarity with data modeling, schema management, and data reliability concepts
• Experience operating systems in an agile, collaborative engineering team

Skills

• Strong experience writing production Python code
• Experience building and supporting pipelines on Azure or an equivalent cloud platform (AWS/GCP)
• Hands-on experience with distributed data processing, such as: Apache Spark, Databricks (or Spark runners such as EMR, Dataproc)
• Experience working with event streaming or messaging platforms, such as: Azure Event Hubs, Apache Kafka / Confluent Kafka, Amazon Kinesis
• Practical experience with CI/CD pipelines, version control, and automated deployments
• Familiarity with data modeling, schema management, and data reliability concepts
• Experience operating systems in an agile, collaborative engineering team

Benefits

Annual Salary Range: $92,100.00 - $138,200.00 May be eligible for bonus and equity.

Benefits:

• Paid sick, vacation, and holiday time
• Paid time off with no specified limit as needed for sick, vacation, bereavement, jury duty, holidays, floating holiday, etc. subject to manager approval