Data & AI Specialist

Career Area:

Engineering

Job Description:

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.

Position Summary

The Data & AI Specialist is responsible for developing and enabling the factory's data and AI capabilities through data governance, data architecture, analytics platforms, and AI solution deployment.

This role serves as the subject matter expert for manufacturing data and AI technologies, driving the establishment of data standards, data quality systems, digital platforms, and AI applications that support operational excellence and smart manufacturing transformation.

The position works closely with Operations, Engineering, Quality, Supply Chain, IT, and business stakeholders to unlock business value from data and AI.

Key Responsibilities

Data Governance & Data Standards

Establish and maintain the factory data governance framework, standards, and best practices.

Define and manage:

Data quality rules

Data quality monitoring KPIs

Data ownership and stewardship processes

Data lifecycle management standards

Develop and maintain Data Owner and Data Steward responsibility matrices.

Conduct regular data quality assessments and drive corrective actions.

Ensure consistency, accuracy, completeness, and reliability of critical business data.

Data Architecture & Master Data Management

Design and maintain manufacturing data models and data architecture.

Develop and govern:

Master data standards

Data dictionary

Metadata management

Naming conventions

Data flow documentation

Establish common KPI definitions and business metric standards across functions.

Support enterprise-wide master data governance initiatives.

Data Collection & Integration

Drive structured digital data collection at the source to reduce manual spreadsheets and offline records.

Design and implement automated data acquisition solutions.

Integrate data from:

ERP systems

MES systems

Quality systems

Supply chain systems

Production equipment

IoT devices

Define data interface standards and integration requirements.

Support development of scalable data pipelines and digital platforms.

Analytics Platform & Decision Support

Support development and optimization of data warehouse and analytics solutions.

Build and maintain data models that enable operational and management reporting.

Develop dashboards and visualization solutions using enterprise BI platforms.

Translate business requirements into meaningful insights and performance indicators.

Enable self-service analytics capabilities for business users.

AI Strategy & Use Case Development

Support development of factory AI roadmap aligned with smart manufacturing and business strategies.

Identify, evaluate, and prioritize high-value AI use cases.

Establish processes for:

AI opportunity assessment

Feasibility analysis

Solution validation

Benefits tracking

Monitor emerging AI technologies and evaluate business applicability.

AI Solution Deployment

Lead and support implementation of manufacturing AI applications, including:

Computer Vision

Automated Quality Inspection

Predictive Maintenance

Process Optimization

Production Scheduling Optimization

Quality Analytics

Root Cause Analysis

Safety Monitoring

Energy Management

Work closely with business teams, IT partners, and vendors to ensure successful deployment and adoption.

Generative AI & Productivity Enablement

Drive GenAI adoption across the factory through:

Knowledge management solutions

Enterprise knowledge bases

Digital assistants and AI agents

Copilot enablement

Workflow automation

Power Platform applications

Office productivity automation

Promote practical GenAI use cases that improve employee productivity and business efficiency.

AI Governance & Risk Management

Support establishment of AI governance processes and standards.

Monitor AI solution performance and business outcomes.

Assist in managing:

Model lifecycle

Compliance requirements

Data privacy

Risk controls

AI usage guidelines

Ensure responsible and sustainable AI implementation.

Data Security & Compliance

Support implementation of data security and access control policies.

Ensure compliance with corporate data governance requirements.

Define data retention and archival standards.

Protect sensitive business and operational information.

Capability Building & Training

Promote data-driven decision making across the factory.

Develop and deliver training programs on:

Data literacy

Analytics

AI fundamentals

GenAI tools

Citizen development

Power Platform

Coach business teams on data and AI best practices.

Qualifications

Education

Bachelor's degree or higher in:

Data Science

Computer Science

Information Systems

Industrial Engineering

Manufacturing Engineering

Artificial Intelligence

Statistics

Related disciplines

Experience

5+ years of experience in data analytics, data engineering, digital transformation, AI, or manufacturing systems.

Experience implementing data governance programs.

Experience with manufacturing data environments preferred.

Experience delivering analytics or AI solutions in industrial settings preferred.