Collect, clean, and validate large volumes of engineering and operational data from diverse sources including sensors, simulation outputs, and enterprise systems. Develop and maintain dashboards and reports using tools such as Tableau, Power BI, or Python-based visualization libraries to monitor system performance and project KPIs. Perform statistical analysis and predictive modeling to identify patterns, root causes of failures, and opportunities for process optimization. Collaborate with design, manufacturing, and R&D teams to translate business and engineering requirements into data solutions. Automate routine data processing tasks using Python, SQL, or scripting languages to improve efficiency and reduce manual errors. Conduct A/B testing and experimental analysis to evaluate the impact of design changes or operational adjustments. Prepare comprehensive data summaries and executive presentations to communicate findings to technical and non-technical stakeholders. Ensure data integr...