Entry Level Validation Engineer

Responsible for testing, analyzing, processing, and reporting standard vehicle-level NVH benchmark test data to support competitive assessments, program tracking, and objective decision-making. The role focuses on repeatable testing, data processing, standardized metrics, and consistent reporting, rather than experimental test development.

• NVH Vehicle Benchmark Testing

  • Coordinate and conduct standard NVH vehicle-level benchmark testing

  • Work with Union Mechanics / Technicians

  • Support process improvement actions in the organization to improve operational and economic efficiencies

• NVH Benchmark Data Processing

  • Access, organize, and process standard NVH vehicle-level benchmark test data from approved test events and internal databases.

  • Apply established digital signal processing methods (filtering, windowing, integration, time/frequency transforms) using standard NVH workflows.

  • Ensure consistency of channel naming, units, test conditions, and signal post-processing across benchmark datasets.

  • Maintain traceability between raw data, processed data, and reported results.

• Data Analysis & Interpretation

  • Execute standardized NVH metrics and KPIs for vehicle-level benchmarking (e.g., overall levels, order content, band limited metrics, event-based metrics).

  • Perform direct vehicle-to-vehicle and configuration-to-configuration comparisons using consistent analysis methods.

• Reporting & Deliverables

  • Generate standard NVH benchmark reports following approved templates and formats.

  • Populate tables, plots, and summaries that clearly highlight competitive performance and relative rankings.

  • Ensure reports are technically accurate, repeatable, and suitable for engineering and management review.

  • Support continuous refinement of standard benchmark report formats and metrics.

• Tool Utilization & Data Management

  • Analyze and post-process data using industry-standard NVH software (Siemens Simcenter Testlab).

  • Use scripting, batch processing, or automated workflows where applicable to improve efficiency and consistency.

  • Archive processed data and reports in standard NVH data management systems following established conventions.

  • Document analysis assumptions, processing settings, and limitations for future reuse.

• Quality & Process Compliance

  • Apply quality checks to confirm data completeness, processing correctness, and metric validity.

  • Verify that benchmark analyses comply with internal NVH standards and test protocols.