Datenanalyse, Prozessoptimierung, Projektmanagement
Nächstmöglicher Zeitpunkt
Navi Mumbai, Maharashtra, India
We are seeking a highly skilled and motivated engineer to join our team in driving digital transformation across manufacturing operations. The ideal candidate will have hands-on experience in asset performance monitoring, predictive analytics, and manufacturing data analysis, with a strong foundation in Chemical or Mechanical Engineering. This role demands multitasking across various digital tools and cross-functional teams to ensure seamless integration and optimization of manufacturing processes. Strong presentation skills and a customer-centric approach are essential to effectively communicate insights and deliver value to stakeholders.
- Implement and manage Asset Performance Monitoring (APM) solutions to improve equipment reliability and reduce downtime.
- Analyze manufacturing process data to identify trends, anomalies, and opportunities for optimization.
- Develop predictive models using historical and real-time data to support proactive maintenance strategies.
- Collaborate with cross-functional teams including operations, maintenance, and IT to integrate analytics into decision-making processes.
- Create dashboards and visualizations to communicate insights using tools like Power BI.
- Support deployment and scaling of digital tools across multiple manufacturing sites.
- Efficiently multitask across various platforms and projects to meet operational goals.
- Present findings and recommendations clearly to technical and non-technical audiences.
- Maintain a customer-centric mindset to ensure solutions align with business needs and operational goals.
- APM Tools:
- Aspen Mtell / Aveva PRiSM / GE Digital Predix APM
- Manufacturing Data Analytics Tools:
- Industrial Data Historians:
- Aspen IP.21 / OSIsoft PI System
- Programming & Scripting:
- Visualization & Reporting:
- ERP Systems:
- SAP PM (Plant Maintenance)
- SAP MM (Materials Management)
- Bachelor’s degree in Chemical Engineering or Mechanical Engineering.
- 4–6 years of relevant experience in manufacturing analytics, reliability engineering, or digital transformation.
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management abilities.
- Strong presentation and communication skills
- Experience in chemical, petrochemical, or process industries.
- Familiarity with industrial data historians like Aspen IP.21 and PI System.
- Knowledge of machine learning techniques for predictive maintenance.
- Ability to multitask and manage multiple digital initiatives simultaneously.
- Customer-Centric approach