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Caterpillar

Makes heavy machinery, engines and gas turbines

Data & AI Specialist

Data ManagementUpdated on Nov 9
Full-timeWujiang, Suzhou, Jiangsu, ChinaNo salary listed

About the Job

Requirements

  • A bachelor's degree or higher in Data Science, Computer Science, Information Systems, Industrial Engineering, Manufacturing Engineering, Artificial Intelligence, Statistics, or a related discipline.
  • At least five years of experience in data analytics, data engineering, digital transformation, AI, or manufacturing systems.
  • Experience implementing data governance programs.
  • Strong experience with data governance, master data management, data modeling, SQL, data warehousing, ETL/ELT processes, Power BI, Azure Data Platform, AI and machine learning fundamentals, generative AI technologies, Microsoft Copilot, and Power Platform.
  • Knowledge of manufacturing systems, including SAP/ERP, MES, IoT platforms, SCADA, and historian systems.

Responsibilities

  • 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, and 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.
  • Design and maintain manufacturing data models and data architecture.
  • Develop and govern master data standards, a data dictionary, metadata management, naming conventions, and data flow documentation.
  • Establish common KPI definitions and business metric standards across functions.
  • Support enterprise-wide master data governance initiatives.
  • 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, and IoT devices.
  • Define data interface standards and integration requirements.
  • Support development of scalable data pipelines and digital platforms.
  • 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.
  • Support development of the 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, and benefits tracking.
  • Monitor emerging AI technologies and evaluate their business applicability.
  • 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, and energy management.
  • Work with business teams, IT partners, and vendors to ensure successful deployment and adoption of AI solutions.
  • Drive generative AI adoption across the factory through knowledge management solutions, enterprise knowledge bases, digital assistants and AI agents, Copilot enablement, workflow automation, Power Platform applications, and office productivity automation.
  • Promote practical generative AI use cases that improve employee productivity and business efficiency.
  • 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, and AI usage guidelines.
  • Ensure responsible and sustainable AI implementation.
  • 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.
  • Promote data-driven decision making across the factory.
  • Develop and deliver training programs on data literacy, analytics, AI fundamentals, generative AI tools, citizen development, and Power Platform.
  • Coach business teams on data and AI best practices.
  • Work onsite in the office five days a week.

Desired Qualifications

  • Experience with manufacturing data environments.
  • Experience delivering analytics or AI solutions in industrial settings.
  • CDMP (Certified Data Management Professional).
  • DAMA data governance knowledge.
  • Microsoft Fabric, Azure AI, or equivalent cloud certifications.
  • Experience in Industry 4.0 or smart manufacturing programs.
  • Experience deploying AI solutions in manufacturing environments.

About the Company

Caterpillar

Makes heavy machinery, engines and gas turbines

Caterpillar makes construction and mining machines, diesel and natural gas engines, industrial gas turbines and locomotives for contractors, mines, energy companies and data center builders. It is the world's largest maker of construction and mining equipment, and its yellow Cat bulldozers and excavators work in nearly every country. Customers buy or rent machines through independent Cat dealers, while its engines and turbines generate electricity and push natural gas through pipelines. Caterpillar earns money from equipment sales and from the parts and repairs that dealers supply over a machine's working life. It was formed in 1925 when California's Holt and Best tractor companies merged, and it is based in Irving, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Irving, TX
Founded
1925

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