30 Jul
|
Tata Electronics
|
Dholera
30 Jul
Tata Electronics
Dholera
Job ID: 40965
Date: 28 Jul 2026
Location
Dholera, GJ, IN
Department: Fab Industrial Engineering and Planning
Business: Semifab
ABOUT THE COMPANY:
Tata Electronics Private Limited (TEPL) is a greenfield venture of the Tata Group with expertise in manufacturing precision components. Tata Electronics (a wholly owned subsidiary of Tata Sons Pvt. Ltd.) is building India’s first AI-enabled state-of-the-art Semiconductor Foundry. This facility will produce chips for applications such as power management IC, display drivers, microcontrollers (MCU) and high-performance computing logic, addressing the growing demand in markets such as automotive, computing and data storage, wireless communications and artificial intelligence.
Tata Electronics is a subsidiary of the Tata group. The Tata Group operates in more than 100 countries across six continents, with the mission 'To improve the quality of life of the communities we serve globally, through long term stakeholder value creation based on leadership with Trust.’
Key Responsibility
Analyze complex project/operational schedules to identify optimization opportunities
Perform critical path and network analysis (CPM)
to improve overall timelines
Identify bottlenecks, constraints, and inefficiencies in workflows
Drive schedule optimization, what-if analysis, and scenario simulation
Work on capacity planning and throughput improvement
Collaborate with engineering and operations to improve flow and reduce delays
Build advanced analytical models, dashboards, and insights using Excel
Support decision-making through data-driven schedule insights
Qualification
5–7 years in construction/project scheduling (focus on planning/analysis)
Solid expertise in CPM, network logic, and schedule optimization
Proficiency in Primavera P6 / MS Project
Advanced skills in Excel (Pivot Tables, Lookups, Data Modeling, Scenario Analysis)
Solid analytical and problem-solving mindset
Experience working with complex, interdependent schedules
Nice to Have
Experience in large-scale industrial or plant projects
Exposure to data tools (Power BI, Python, VBA)
Background in process optimization or industrial engineering concepts
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