• Design, develop, and maintain production-grade Python and Java data services and pipelines deployed on Google Cloud Platform. • Build and evolve Google Cloud Dataflow batch and streaming pipelines for data ingestion, standardization, curation, and analytics load. • Implement and maintain event-driven data workflows using Google Cloud Pub/Sub. • Design and manage BigQuery datasets, table schemas, partitioning strategies, clustering, and reporting views. • Build and maintain Cloud Composer (Apache Airflow) DAGs for workflow orchestration. • Develop and maintain Cloud Run microservices and Cloud Functions. • Participate in design and code reviews; mentor junior engineers and contribute to shared coding standards. • Collaborate with teams to ensure on-time delivery and best engineering practices. • Engage proactively in the triage and resolution of escalated production issues. • Follow and comply with all security policies and procedures established by the organization, including adherence to HIPAA and HITRUST regulations.

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.