Data Engineer

Role Overview

Edmunds is looking for a Data Engineer to architect and scale foundational data platforms that power analytics, AI/ML, and business intelligence. You’ll lead the transition to real-time, data-driven decisioning, designing how Edmunds leverages data across the enterprise—not just maintaining pipelines.

Responsibilities

• Pipeline Architecture: Build and maintain scalable, reliable batch and real-time pipelines for structured and unstructured data.
• Platform Leadership: Enhance and maintain the data lakehouse used for core decision-making.
• Core Systems Engineering: Hands-on work with transactions and pricing pipelines, optimizing data workflows.
• Process Engineering: Improve internal processes by automating manual work, optimizing data delivery, and redesigning infrastructure for scalability.
• Infrastructure & Cloud: Support and build data infrastructure on AWS.
• Cross-functional Collaboration: Partner with Executive, Product, and Data teams to address technical data needs.
• Technical Guidance: Design solutions, troubleshoot pipeline issues, ensure data quality, and align changes with business goals and engineering best practices.

Requirements

• High proficiency in at least one object-oriented or functional programming language (codebase largely in Scala and Python).
• Strong SQL skills and proven experience writing ETL jobs and working with data at scale.
• Experience with real-time / streaming pipelines.
• Familiarity with some of: Spark, Scala, Python, AWS, Databricks, Airflow.
• Ability to design maintainable software using engineering best practices and design patterns/algorithms.
• Experience modernizing and evolving existing systems.
• Strong problem-solving, troubleshooting, and communication skills, especially in a hybrid/remote environment.

Nice-to-have

• Broader familiarity with cloud-based data platforms (text cut off, but indicates additional platform/deployment expectations).