Lead Data Engineer - Physical AI Platform, Data Engineering

Career Area

Technology, Digital and Data

Your Work Shapes the World at Caterpillar Inc.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live.

Together, we are building a better world, so we can all enjoy living in it.

Help Build the Future of Caterpillar – At Caterpillar, technology always has a purpose, which is to solve our customers’ toughest challenges. Through Cat Technology, we are solving problems by building the intelligence layer that connects machines, data, and people to make jobsites safer, more productive, and more sustainable. By combining deep domain expertise in physical systems with software, connectivity, autonomy, and AI, we deliver solutions that work in the real world—on real jobsites, at global scale.

You’ll build and deploy against one of the most unique data foundations—over 1.6 million connected assets generating real‑world data daily. These data and platform capabilities are enabling the development of AI models, edge computing architectures, and software systems that scale across fleets, products, and industries. The result will be a new generation of machines that continuously learn, improve, and deliver performance at scale.

Be Part of What’s Next in Autonomous Construction Sites. Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible—intelligent machines operating in dynamic jobsites—into reality.

Our connected ecosystem brings together massive volumes of high-quality data to create a foundation where engineers like you can build and deploy against.

In these roles, you’ll work at the intersection of the physical and digital worlds. You’ll help design and deliver intelligent systems that enable machines to perceive their environment, make informed decisions, and support safer, more productive operations.

As a Lead Data Engineer, you will design, build, and maintain scalable data pipelines, microservices, and cloud-based data platforms that deliver reliable, high-quality data for business and engineering teams. Working in an agile environment, you will help drive data architecture, performance, reliability, and continuous improvement across modern data solutions.

• Actively collaborate with Principal Software Engineers and Data Architects to define solution architecture
• Lead the solution design and optimization of scalable data pipelines and microservices in Python, enabling both real-time and batch data processing across enterprise platforms
• Drive the development of cloud-native data ingestion and streaming solutions leveraging AWS services including Kinesis, S3, DynamoDB, Event Bridge, and related technologies
• Own the design, implementation, and operational excellence of data integration frameworks and source data pipelines supporting CI Autonomy initiatives
• Partner with business, product, and engineering stakeholders to translate complex requirements into scalable data architectures, workflows, mappings, and system designs
• Establish and enforce automated testing, data quality controls, and validation frameworks to ensure integrity, reliability, and compliance across distributed data ecosystems
• Lead operational monitoring, performance tuning, and root-cause analysis of production data platforms using observability tools such as Cloud Watch to maintain high availability and service reliability

• Decision Making and Critical Thinking:
  Ability to lead the analysis and resolution of complex issues within distributed data platforms, designing scalable, and resilient solutions
• Effective Communications:
  Ability to communicate across teams by sharing feedback constructively, listening to others, and creating documentation that makes data systems and processes easy to…