Data Engineer - Cloud Analytics & Data Lake (Onsite)

John Deere; East Moline (IL); On-site; USD 87,000 - 130,000; Full time

Benefits offered by this job

Flexible work arrangements

Competitive base pay

Healthcare benefits

Tuition assistance

On-site gyms

Job summary

John Deere is seeking a Software/Data Engineer to join the Dealer Data Lake team in East Moline, IL or Chicago. You will design and build enterprise data pipelines, develop data models, and deliver analytics solutions that drive dealer operations.

You will work with Python, Spark, SQL, and modern cloud platforms, contributing to CI/CD automation and robust data governance. This role emphasizes collaboration with cross-functional teams and hands-on data engineering in a large enterprise.

Qualifications

• BS/MS in computer science or related field with data focus.
• Strong experience in data engineering and analytics.
• Proficiency in Python, Spark, SQL, and cloud platforms.

Responsibilities

• Design, build, and maintain scalable data pipelines and analytics.
• Develop data models to support BI and advanced analytics.
• Create and maintain data products for dealer analytics environments.
• Collaborate to improve platform reliability, scalability, and performance.
• Participate in architecture decisions and CI/CD practices.
• Monitor data quality and resolve data defects in production.
• Document data flows and engineering processes.

Skills

Python

Apache Spark

Microsoft Fabric

CI/CD

GitHub Actions

SQL

ETL/ELT

Data modeling

Data quality

Dynamics FO/CRM

Education

Bachelor's degree in computer science or related

Master's degree preferred

Tools

Databricks

Microsoft Azure

Power BI

Job description

John Deere is seeking a Software/Data Engineer to join the Dealer Data Lake team in East Moline, IL or Chicago. You will design and build enterprise data pipelines, develop data models, and deliver analytics solutions that drive dealer operations.

You will work with Python, Spark, SQL, and modern cloud platforms, contributing to CI/CD automation and robust data governance. This role emphasizes collaboration with cross-functional teams and hands-on data engineering in a large enterprise.