Full-Stack Data Engineer

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS

MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who possesses a strong passion for designing, optimizing, refactoring, and upgrading complex data solutions! MOTOR’s primary product is Automotive Content, and we need someone who can help us support our Insights-based product suite.

We are looking for someone who wants to be part of our mission to transform the future. We have a rare opportunity for you to use your talent, passion, and expertise to help drive this massive change in how we build our user experience across our product lines, and how consumers experience the MOTOR Product Platform.

This position offers excellent career growth and promotional opportunities, stellar compensation, and the ability to work with the world's premier provider of aftermarket automotive data. Hearst / MOTOR Information Systems will be the best and last place you’ll ever work!

Required Experience (Must Have)

Expert Python Developer

Strong SQL Developer

Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift)

Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet)

Strong Automation Experience

Experience with Databricks (Delta Lake, Notebooks, SQL Analytics)

Experience with Kubernetes (Cluster Orchestration, Container Networking, Pod Management)

Experience with DevOps, CI / CD, Deployment Orchestration (Octopus Deploy)

Experience with Git and Azure DevOps

Experience with Agentic AI (LangGraph, MCP Servers, Agent Frameworks)

Experience with Data Handling (Pandas / NumPy, Apache Spark, Ray)

Helpful Experience (Nice to Have)

Experience with LLMs, Machine Learning & Deep Learning Libraries, AI Application Frameworks, Vector Databases

Experience with Automotive Data / Industry

Experience with Agile / Scrum

Primary Responsibilities

• Analyze large, and complex, data sets
• Design, develop and coordinate the generation of Data Pipelines
• Work collaboratively with team to plan and solve complex problems
• Design for, or optimize existing pipelines, for performance and cost

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