Data Engineer – Physical AI Platform

Build reliable, high-performance data systems for Physical AI. As a Data Engineer in Caterpillar’s Physical AI Platform team, you will design, build, and maintain scalable data pipelines, microservices, and cloud-based data systems with an emphasis on performance, reliability, and data quality. The role is based onsite in Irving, TX (Dallas) and includes a competitive pay range of $97,530 - $158,480 per year.

What you’ll work on

You will create end-to-end data workflows for both real-time and batch processing, translating requirements into data mappings and system designs. Work includes implementing automated testing and validation to protect data integrity across distributed systems, plus monitoring and troubleshooting to keep pipelines running smoothly.

• Design, build, and optimize data pipelines and microservices using Python for real-time and batch processing
• Develop AWS-based cloud data ingestion solutions using services such as Kinesis, S3, DynamoDB, and EventBridge
• Build and maintain data integration workflows for source data pipelines aligned to CI Autonomy
• Translate business needs into reliable data workflows, mappings, and system designs
• Implement automated testing and validation to ensure data integrity across distributed systems
• Monitor and troubleshoot pipelines using CloudWatch to maintain reliability

Key skills and experience

• Ability to analyze issues in distributed data systems and deliver scalable solutions
• Ability to clearly document data flows, mappings, and system behavior for cross-team use
• Experience building backend systems and pipelines with Python and Java, using modern frameworks
• Experience delivering solutions in an agile environment
• Experience integrating APIs, streaming platforms, and databases
• Ability to design scalable, event-driven data systems
• Strong understanding of AWS services and data engineering tooling
• Experience implementing testing strategies to ensure data quality and system reliability

Preferred background

• Bachelor’s degree in Computer Science, Computer Engineering, or related field
• 2+ years development experience on modern, large-scale, complex data platforms
• 3+ years developing and deploying Java or Python solutions to production
• Experience building high-throughput, scalable data pipelines
• Hands-on AWS data services experience (Kinesis, S3, DynamoDB, EventBridge, etc.)
• Proficiency in SQL, including data quality and validation practices
• Experience deploying with CI/CD tools such as Azure DevOps, Jira, and Jenkins
• Experience developing microservices for real-time data ingestion
• Experience with relational and noSQL databases
• Ability to ensure data integrity across distributed and streaming systems
• Experience with API development and secure integrations (such as OAuth 2.0)
• Proven experience with monitoring, testing, and automation in large-scale data environments

Technology areas you’ll use

Python, Java, AWS, Kinesis, S3, DynamoDB, EventBridge, event-driven data systems, CloudWatch, SQL, plus CI/CD tools (including Azure DevOps, Jira, Jenkins) and related development tools. Experience with OAuth 2.0, microservices, and distributed systems is also relevant.

Benefits and support

• Medical, dental, and vision benefits
• Paid time off plan (Vacation, Holidays, Volunteer, etc.)
• 401(k) savings plans
• Health Savings Account (HSA) and Flexible Spending Accounts (FSAs)
• Health Lifestyle Programs
• Employee Assistance Program
• Voluntary Benefits and Employee Discounts
• Career Development
• Incentive bonus
• Disability benefits
• Life Insurance
• Parental leave and Adoption benefits
• Tuition Reimbursement

Additional details

• Full-time role working onsite at the Irving, TX office (Dallas)
• Domestic relocation assistance is available
• Visa sponsorship is available
• Employment is conditioned upon successful completion of a drug screen

Caterpillar is an Equal Opportunity Employer, including Veterans and Individuals with Disabilities. Qualified applicants of any age are encouraged to apply.