Principal - Data Management, Business Risk Intelligence

Cummins•Columbus, IN

About The Position

Cummins is seeking a Principal - Data Management, Business Risk Intelligence to join its Systems/IT team in the Corporate organization in Columbus, Indiana. This role leads the development of secure technology solutions and the integration, optimization, and architecture of systems that meet business, performance, security, and compliance requirements. It advances cybersecurity through engineering, research, secure design, and penetration testing, while contributing to financial planning and leading employees, contractors, and other resources. The role also builds cross-organizational relationships to deliver measurable business value and cybersecurity outcomes. The position defines and maintains the Business Risk Intelligence (BRI) data strategy and roadmap, establishing enterprise data capabilities for emerging-risk identification, executive decision support, and intelligence-driven risk management. It aligns data initiatives with enterprise risk priorities, AI strategy, and business objectives; integrates risk information from internal functions and external intelligence sources; and establishes data standards and governance to improve ownership, quality, consistency, accessibility, and lifecycle management. The role develops AI-ready data models for predictive analytics, generative AI, knowledge management, and executive reporting. In partnership with the Automation Specialist, it implements AI-enabled intelligence and advanced analytics, evaluates emerging AI technologies, and promotes responsible AI practices. It correlates risk data to identify trends and relationships, supports Key Risk Indicators, Early Warning Indicators, and executive dashboards, and ensures BRI capabilities integrate with relevant enterprise risk, security, analytics, and AI platforms.

Requirements

College, university, or equivalent degree in Computer Science, Information Technology, a related subject, or relevant equivalent experience.
5–7 years of cybersecurity work experience.
Experience in enterprise data management, analytics, AI, business intelligence, or cybersecurity.
Knowledge of data governance, Power BI, SQL, Microsoft Fabric/Azure, AI technologies, and enterprise risk management is identified as preferred in the qualifications.

Nice To Haves

CISSP or similar certification.
Two years of experience with cloud technology and concepts.
Knowledge of data governance, Power BI, SQL, Microsoft Fabric/Azure, AI technologies, and enterprise risk management.

Responsibilities

Lead the development and implementation of secure technology solutions with stakeholders, aligning cybersecurity capabilities with business needs.
Drive integration and optimization of cybersecurity system configurations to meet performance, security, and compliance requirements.
Conduct system engineering and research to develop security solutions supporting strategic business objectives.
Design secure hardware, operating systems, and software architectures that address cybersecurity risks and protect business assets.
Oversee penetration testing, identify vulnerabilities, and ensure appropriate remediation.
Contribute to budgeting, forecasting, annual operating plans, purchase order management, and financial oversight.
Lead, coach, and develop teams, managing employees, contractors, and resources to deliver immediate and strategic goals.
Build organizational relationships and use Business Relationship Management practices to deliver business value and cybersecurity outcomes.
Define and maintain the Business Risk Intelligence data strategy and roadmap.
Establish enterprise data capabilities for emerging-risk identification, executive decision support, and intelligence-driven risk management.
Align data management initiatives with enterprise risk priorities, AI strategy, and business objectives.
Integrate and manage enterprise risk data from Cybersecurity, Enterprise Risk, Audit, Compliance, Privacy, Legal, Supply Chain, Operational Technology, Finance, and external intelligence sources.
Establish standards for enterprise risk data classification, ownership, metadata, and lifecycle management.
Improve data quality, consistency, and accessibility to support trusted intelligence and analytics.
Develop AI-ready data models for predictive analytics, generative AI, knowledge management, and executive reporting.
Partner with the Automation Specialist to implement AI-enabled intelligence capabilities and advanced analytics.
Evaluate emerging AI technologies and promote responsible AI practices within the BRI capability.
Correlate enterprise risk data to identify trends, emerging risks, and cross-domain relationships.
Develop data models for Key Risk Indicators, Early Warning Indicators, and executive dashboards.
Enable intelligence-driven insights to improve enterprise risk prioritization and decision-making.
Partner with Enterprise Data & Analytics, Cybersecurity, Enterprise Risk Management, Audit, Compliance, Privacy, Legal, Digital, and IT teams.
Establish governance processes for enterprise risk data ownership, stewardship, and quality.
Ensure BRI data capabilities integrate with GRC, vulnerability management, threat intelligence, operational technology, business intelligence, and AI platforms.