What you'll do:Eaton is a diversified power management company providing energy-efficient solutions that help our customers effectively manage electrical, hydraulic and mechanical power. The company is a global technology leader in aerospace fuel, hydraulic, electric and actuation systems for commercial and military use; and truck and automotive drivetrain and powertrain systems for performance, fuel economy and safety; electrical products, systems and services for power quality, distribution, control, and transmission. Eaton India Innovation Center (EIIC) has an opening for Lead System Engineer - Data Centers This position will be based in Pune, India.
EIIC Office of Chief Engineer (OCE) organization is aligned to CTO's strategy to drive "One Eaton Engineering Excellence". EIIC OCE will work with global Engineering business engineering leaders from Electrical and Industrial Sector businesses.
The position will be responsible for systems engineering activities, pertaining to electrical systems, with initial focus on Data Centers. Responsibilities include systems modeling, systems requirements, system architecture/ design tradeoffs for Electrical Systems. Activities would span systems engineering, modelling and validation activities for new product development including, analyzing requirements and assessing compliance, defining interfaces, flowdown of system requirements to subsystems & components, system architecture design tradeoffs, around Systems Engineering (SE) centric methodologies, processes and practices.
A successful candidate will need knowledge and prior experience in systems engineering pertaining to Electrical Systems product development process at system and subsystem levels, and serve as an practitioner in systems engineering, and ensure mature systems engineering processes, including adoption of relevant tools across the systems engineering lifecycle.
• Apply systems engineering and MBSE principles to define, model, analyze, and evaluate complex data center electrical and infrastructure architectures.
• Develop and maintain system-level architecture models spanning requirements, functional, logical, and physical views for data center applications.
• Integrate multi-domain models across electrical power, thermal management, controls, cooling infrastructure, mechanical systems, software, and IT load domains.
• Establish modeling assumptions, interfaces, abstraction levels, and interoperability standards to ensure consistency across architecture and performance models.
• Connect architecture models with discipline-specific analysis models using standards and workflows such as FMU, co-simulation, and digital engineering toolchains.
• Model coupled system behaviors including electrical losses, thermal response, control strategies, reliability considerations, and operational scenarios.
• Perform electrical system analyses such as steady-state and transient studies, power flow, efficiency and loss modeling, fault analysis, protection coordination, and disturbance response.
• Analyze data center power distribution architectures from utility interface and MV/LV distribution through UPS, switchgear, transformers, PDUs, rack-level distribution, and IT loads.
• Evaluate conventional and emerging architectures, including centralized versus distributed power conversion, modular blocks, scalable designs, and alternative power delivery approaches.
• Conduct multi-attribute trade-space analysis to support architecture down-selection using metrics such as cost, efficiency, energy use, thermal performance, availability, resilience, footprint, maintainability, and scalability.
Qualifications:- Engineering Graduate/ Post Graduate / PhD in electrical engineering / electronics engineering or Equivalent
- Overall min 12+ years of relevant experience in systems engineering (electrical power systems)
- • Strong expertise in systems engineering and MBSE, including CONOPS, requirements, functional/logical/physical architecture, interfaces, behaviors, operational scenarios, and verification traceability.
• 10+ years of experience in electrical systems engineering, system modeling, power systems analysis, or data center infrastructure engineering.
• Demonstrated ability to apply MBSE methods to complex engineered systems, including model structure, abstraction levels, reusable architecture patterns, interface definition, and digital-thread implementation.
• Hands-on experience with electrical system simulation and analysis tools such as MATLAB/Simulink, ETAP, SKM, PSCAD or equivalent platforms.
• Proven experience modeling data center or large-scale industrial power distribution systems, including utility interface, MV/LV distribution, transformers, switchgear, UPS, PDUs, busway, rack-level distribution, and IT loads.
• Strong requirements engineering capability, including stakeholder needs capture, requirements development, flow-down, allocation, compliance management, traceability, and change impact analysis.
• Expertise in system architecture, control system modeling, operating modes, state behavior, source-transfer scenarios, disturbance response, and control-loop dynamics.
• Knowledge of applicable data center, electrical safety, power quality, and systems engineering standards, including relevant UL, IEC, IEEE, ISO/IEC 15288, and data center KPI frameworks.
• Strong understanding of electrical power studies, including load flow, equipment loading, voltage drop, power factor, harmonics, short-circuit analysis, fault duty, protection coordination, selectivity, transient stability, voltage/frequency recovery, and grid interaction at the point of common coupling.
• Ability to connect requirements, architecture, load assumptions, static analysis, dynamic analysis, cost/footprint models, reliability models, and KPI rollups into a coherent digital thread.
• Working knowledge of multi-domain and multi-physics modeling across electrical, thermal, cooling/fluid, controls, mechanical, software, reliability, and IT load domains.
• Familiarity with thermal and cooling analysis concepts relevant to data centers, including electrical losses as heat sources, coolant flow, temperature margins, cooling power, PUE, WUE, and thermal constraints on rack density.
Skills:• Develop decision-support models that quantify architectural trade-offs and translate modeling results into clear, evidence-based recommendations.
• Validate models against design data, test results, vendor inputs, and operational scenarios to ensure appropriate fidelity and credibility.
• Collaborate with architecture, electrical hardware, thermal, controls, software, mechanical, reliability, and program teams to align models, assumptions, interfaces, and decisions.
• Serve as the technical focal point for data center system modeling, ensuring work is aligned with program objectives, customer needs, and architecture tradeoff workflows.
• Apply and influence modeling methods, standards, and best practices across MBSE, electrical analysis, thermal-fluid modeling, controls simulation, reliability analysis, optimization, and CAD-enabled workflows.
• Use relevant tools such as CATIA Magic, IBM Rhapsody, DOORS, JAZZ, MATLAB/Simulink, ETAP, SKM, PSCAD, or equivalent platforms.
• Communicate complex modeling outcomes to technical leadership, customers, and stakeholders through concise, decision-ready narratives.
• Experience with reliability, availability, maintainability, and resilience analysis, including redundancy architectures, N/N+1/2N concepts, single points of failure, MTBF/RBD concepts, expected downtime, and operational risk scenarios.
• Ability to perform multi-attribute trade-space analysis using constraints, objectives, scenarios, sensitivity analysis, Pareto comparison, weighting methods, and decision-ready KPI summaries.
• Experience integrating MBSE (e.g. System Composer), analysis, BIM/Revit, CAD, digital twin, FMU/co-simulation, and data-management workflows to support architecture evaluation and model reuse.
• Strong analytical problem-solving and technical communication skills, with the ability to translate complex modeling results into clear recommendations for technical leaders, customers, and cross-functional stakeholders;
• INCOSE ASEP/CSEP or equivalent systems engineering certification is preferred.
• Good familiarity with MBSE methodologies/ practices
• Exposure to Lean/ Agile methodologies and practices
