Role Description Join Eaton’s Information Technology team to drive business impact with advanced technologies and major enterprise projects. We seek a Principal IT Data Warehouse leader to oversee large, complex initiatives related to the Boyd integration including: - Manage end-to-end integration projects, collaborating with cross-functional teams and senior leaders. - Act as a liaison between business units and technological teams with a focus on Data Warehouse and ERPs. This position reports directly to the VP – IT Boyd Integration Leader. Essential Responsibilities: - Develop and maintain strategic business relationships across Boyd Thermal, Integration and broader IT teams. - Serve as point of contact for IT integration team. - Partner with the Boyd Thermal Business and IT team to integrate Boyd Thermal with Eaton. - Act as IT Business Process owner to translate business requirements to IT requirements. - Partner with business leaders to capture data, reporting, and analytics requirements. - Own end-to-end data warehouse processes, including data ingestion, transformation, and integrations. - Translate business needs into scalable data warehouse solutions and roadmaps. - Align tactical needs and delivery with appropriate broader IT and functional teams. - Partner with IT IMO to ensure best practices are deployed. - Develop and manage the implementation plan for the Boyd IT integration. - Manage quality of the deliverables. - Ensure all requirements have been validated and user acceptance tests have been executed successfully prior to going live. - Communicate and present project status to IT and Business teams. Optional: Advanced understanding of scrum Agile and ability to serve as a PM or scrum master on a scrum project. Qualifications - Bachelor’s degree from an accredited institution. - Minimum ten (10) years of IT experience. - Minimum five (5) years of IT Application experience. - Experienced in supply chain, manufacturing, ERP, commercial and configurations application. - Must be authorized to work in the United States without company sponsorship now or in the future. - Master’s Degree. - PMP Certification. - 5+ years of IT Application experience preferably in a customer or business facing leadership role. - Global leadership experience for a large, multinational corporation. - Experience with M&A, integration, and/or divestitures. Requirements - Experience working in large cross-functional global organizations/teams. - Advanced to SME understanding of business processes of complex, multinational companies. - Experience owning and leading IT teams to ensure delivery of IT projects. - Strong technical knowledge and solid understanding of computer hardware and software, ERP, data management, data warehouse, application programming, data communications, operating systems, utilities and data security. - Intermediate to advanced understanding of financial processes. - Advanced understanding of business industry trends and applicability to operations or functions. - Advanced to SME understanding of integration and impact points of involved systems globally for a division or function. - Proven experience of exhibiting a digital mindset through fostering agility and innovation. - Proven leadership, talent development and management skills for teams in a global setting. - Ability to understand the integration and interdependence between systems and projects. - Strong communication and influence across technical and non-technical audiences. Benefits - Health and Welfare benefits. - Retirement benefits. - Programs that provide for paid and unpaid time away from work.

• Drive the company-wide AI agenda: scaling local AI initiatives into centralized production systems that create measurable business value. • Own broad, high-impact AI initiatives that have cross functional impact: Moving our AI usage from past narrow or siloed automation examples to execute a company operational transformation. • Partner with Product, Engineering, and operational leaders to embed AI capabilities into our customer-facing platform, internal business workflows, and core processes. • Serve as the ultimate technical authority for our data and AI infrastructure, making critical architectural decisions across MLOps pipelines, LLM orchestration frameworks, and distributed data systems. • Oversee the development of a scalable corporate data platform that serves as the foundational bedrock for all AI and machine learning capabilities. • Transform our internal knowledge base by building the systemic data architecture needed to turn unstructured information into intelligent, easily searchable, and actionable assets. • Re-build and evolve our company-wide data structures and connectivity pipelines to be optimized to deploy, run, and maintain AI models efficiently while lowering cost-to-serve. • Set the company wide tooling standards, maintain technical quality guardrails, and establish engineering best practices for embedded AI specialists working within distinct business units. • Actively support the implementation of key local solutions built by decentralized specialists, ensuring they have the tools and centralized platform support required to succeed. • Maintain high levels of ethical compliance by ensuring all global AI initiatives strictly adhere to data privacy, platform security, and ethical compliance standards. • Educate and empower teams across the organization to scale their own AI use productively, providing them with the structural frameworks needed to safely build and innovate within their functions. • Partner deeply with the People and Operations functions to champion organizational AI capability, replacing operational uncertainty with structured technical training loops that convert manual specialists into power-users of automated solutions. • Drive the organizational change management and literacy efforts required to reshape daily workflows, shifting company culture and habits from traditional manual processes to AI-assisted operations.

• Design, build, and maintain scalable data ingestion pipelines supporting a wide range of source systems (APIs, databases, streaming platforms, third-party data providers) • Develop batch and real-time ingestion frameworks capable of handling high data volumes and low-latency requirements • Build fault-tolerant and resilient pipelines with strong guarantees around data integrity, idempotency, and recovery • Establish and enhance observability, monitoring, and alerting for ingestion pipelines (latency, throughput, failures, data freshness) • Implement and enforce data quality checks and validation frameworks at ingestion points • Contribute to the development of Data Ingestion as a platform product, including reusable frameworks, standards, and best practices • Leverage AI-assisted development tools and automation to accelerate pipeline development, improve code quality, and enhance operational efficiency (e.g., code generation, testing, anomaly detection, workflow automation) • Partner with upstream system owners and downstream consumers to define data contracts, SLAs, and schema evolution strategies • Optimize pipelines for performance, cost, and efficiency across compute and storage layers • Use Infrastructure as Code (IaC) to provision and manage ingestion infrastructure in a consistent and scalable manner • Collaborate with platform, analytics, and data science teams to ensure seamless data availability and usability.

• Own pipeline and infrastructure work from intake through production • Build and maintain ingestion and transformation pipelines from operational systems, third-party APIs, and event streams into the warehouse • Turn product and business requirements into specifications and well-modeled datasets • Write and maintain Terraform for the AWS resources your pipelines run on • Use CI/CD to ship pipeline and infrastructure changes safely and often • Build data quality checks, unit tests, and integration tests for the pipelines you own • Use modern tooling, including AI assistants, to move faster on development, testing, and documentation • Build datasets and reporting layers for product features, BI, and operational reporting • Work with Product, Engineering, Operations, Sales, and Compliance so data solutions actually fit the downstream use case • Write the runbooks and documentation that on-call teammates and stakeholders will rely on • Watch your pipelines in production and fix issues before someone has to ask • Keep up with what is changing in data engineering, cloud infrastructure, and fintech compliance