Data-Driven Systems Engineer: Solar Tracking & Electrical

Voltiris; Lausanne; Hybrid; CHF 90.000 - 130.000; Vollzeit

Zusammenfassung

Voltiris in Lausanne is seeking an analytically driven System Engineer to challenge electrical integration and solar tracking systems. This is not maintenance; it tasks you with proving a better model and driving it into industrialized reality, using data rather than opinion.

You will go on-site, travel as needed, and own the data and firmware layer behind tracking accuracy, predictive maintenance, and system health, setting hypotheses and validation methods to reduce complexity and failure

Qualifikationen

• Background in firmware or embedded systems, ideally in motion control or precision positioning.
• Design and run validation methodologies for tracking precision, repeatability, and fault behavior.
• Experience building data-driven monitoring/analytics tools (anomaly detection, predictive maintenance, dashboards).
• Comfort using quantitative performance data to challenge supplier specs or in‑house assumptions.

Aufgaben

• Redesign and validate cabling, network, and tracking architectures using data.
• Reduce failure rate, complexity, and installation time across deployed systems.
• Develop monitoring and predictive maintenance tools for production.
• Be the first call for recurring field issues to understand root causes.

Kenntnisse

Firmware development

Embedded systems

Motion control

Data analytics

Anomaly detection

Predictive maintenance

System health dashboards

Quantitative data analysis

Validation methodologies

Ausbildung

Bachelor/Master/PhD

Jobbeschreibung

Voltiris in Lausanne is seeking an analytically driven System Engineer to challenge electrical integration and solar tracking systems. This is not maintenance; it tasks you with proving a better model and driving it into industrialized reality, using data rather than opinion.

You will go on-site, travel as needed, and own the data and firmware layer behind tracking accuracy, predictive maintenance, and system health, setting hypotheses and validation methods to reduce complexity and failure