Senior Manager, Data Architecture

Caterpillar Inc.•Irving, TX

1d•$172,630 - $258,950•Onsite

About The Position

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. If this work motivates you, we invite you to join our team. 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. Job Summary: The Senior Manager, Data Architecture leads the organization responsible for building the data foundation that enables Physical AI, autonomy, digital twins, and next-generation intelligent systems. This leader defines and delivers the data architecture, data domains, data products, and AI-ready data capabilities required to transform machine, sensor, telemetry, simulation, and operational data into trusted assets that accelerate AI development and autonomous system innovation. Working at the intersection of data, AI, digital twins, and autonomy, this role is accountable for how data is organized, managed, and delivered, ensuring engineers and data scientists can efficiently develop, train, fine-tune, validate, and deploy next-generation AI models while accelerating innovation through scalable and reusable data products. The role is accountable for establishing scalable data patterns that support the full Physical AI lifecycle, including data collection, ingestion, processing, quality, governance, annotation, and availability for model training, fine-tuning, simulation, and deployment. Working closely with perception, robotics, simulation, AI Factory, and engineering teams, this leader ensures that high-quality data flows seamlessly from physical machines and environments into AI development ecosystems and back into continuously improving intelligent systems. Success in this role is measured by the organization’s ability to create reusable data products, enable faster AI model development, improve autonomy performance, and establish a scalable data foundation that allows intelligent machines to learn, adapt, and operate safely in complex physical environments. Bottom line, you are creating the data foundation that enables Physical AI innovation at scale

Requirements

Analytical Thinking: Expert Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
Data Architecture: Expert knowledge of processes, techniques and factors that affect data architecture; ability to design blueprints on how to integrate data resources for business processes and functional support. Ability to utilize design methodologies, tools and techniques to convert business requirements and logical models into a technical design.
Effective Communications: Expert understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors.
Organizational Leadership: Expert knowledge of leadership concepts and ability to use strategies and skills to enlist others in setting, embracing and achieving objectives.
Platform Architecture: Expert knowledge of technologies and methods to design processing mechanisms and roadmaps to execute business application systems; ability to design these roadmaps and deploy supportive interfaces for end-users to access related systems, in accordance with standards and processes.
Team leadership, management and budget responsibility experience (typically 5+ years)
Progressive career in software engineering and architecture with a focus on data (typically 12years+)

Nice To Haves

Data Architecture & Domain Modeling: Demonstrated ability to define enterprise data domains, canonical data models, data contracts, metadata strategies, and scalable architectures that support complex AI and autonomy ecosystems. Strong understanding of data governance, metadata management, data quality, data modeling, and data architecture concepts
AI & Machine Learning Data Foundations: Deep understanding of the data requirements for AI model development, including training data, fine-tuning datasets, feature engineering, vector data, model evaluation data, synthetic data, and data pipelines that support the AI lifecycle.
Data Platforms & Data Products: Experience designing modern cloud and on-premise data platforms and data products architectures for massive data volumes and events, including streaming data, telemetry platforms, APIs, self-service data capabilities, and reusable data assets that accelerate engineering and data science teams.
Physical AI & Industrial Data Ecosystems: Knowledge of machine telemetry, sensor data, digital twins, simulation data, edge-to-cloud architectures, and the unique challenges associated with autonomous systems and real-world operational data. Demonstrated AI systems thinking and judgement, data and model lifecycle leadership, as well as agentic AI and human in the loop solution design.
Strategic Architecture Leadership: Ability to influence senior leaders, define architectural roadmaps, establish standards and patterns, govern technology decisions, and provide technical direction across multiple engineering organizations without direct authority. Demonstratable experience leading technology development for enterprise scale systems in public cloud and hybrid eco-systems

Responsibilities

Leading the team in the delivery of solutions.
Developing strategies, processes, methodologies and best practices for architecture activities.
Providing expert advice and resolving complex problems and issues involved in architecture activities.
Managing architecture projects, while focusing on the maintenance of customer relationships and various resources to ensure high quality deliverables.