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Project engineer - predictive analytics & digital maintenance – frauenfeld

Frauenfeld
Stadler
Projektingenieur
Inserat online seit: Veröffentlicht vor 7 Std.
Beschreibung

Ph3Responsibilities /h3 ul liWork on data driven maintenance projects across the full value chain - from sensors to onboard architecture to communication gateways to off board analytics systems /li liContribute to the development of condition monitoring use cases by identifying how to leverage available data for condition monitoring /li liContribute to the development, design, and scaling of condition monitoring solutions within the Stadler telemetry ecosystem /li liBridge onboard train architectures and off-board analytics systems to identify practical, scalable solutions /li liAnalyze system behavior by tracing control logic and communication flows across trains and their subsystems /li /ul h3Qualifications /h3 ul liFamiliarity with TCMS architecture concepts such as CAN and TRDP /li liBasic Python skills or genuine interest in developing them /li liAbility to analyze and understand software using Function Block Diagrams (FBD) /li liExperience with version control systems for software and documentation, including GitLab or SVN /li liAbility to clearly explain technical concepts and contribute to knowledge exchange in a collaborative, cross-functional team /li liProactive problem solver, comfortable with exploring questions, proposing solutions, and adapting approaches when challenges arise /li liStrong interest in leveraging data to improve maintenance /li liWorking fluency in English and German /li /ul h3Beneficial Skills /h3 ul liExperience with Selectron tools /li liExperience supporting or managing projects, coordinating technical teams to deliver within scope, timeline, and resource constraints /li liExperience creating or guiding visualizations that support effective decision making for engineering, maintenance, and business teams /li liExperience or interest in assessing technical and operational risks, including cyber related threats, and supporting mitigation planning across the digital value chain /li /ul /p #J-18808-Ljbffr

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