Manager-FEA

Job Title: Manager - FEA

Department: R&D

Position Summary

The FEA Manager leads the analysis team responsible for structural, thermal, dynamic and fatigue analysis of components and systems using Finite Element Methods. This role ensures high-quality analytical support for product design, validation, and optimization while managing resources, timelines, and collaboration across design, testing, and manufacturing teams. This position will be located at Blue Star Innovation Centre, Thane, Maharashtra, India.

Key Responsibilities

• Leadership & Management

• Lead and mentor a team of FEA engineers and analysts.
• Plan, prioritize, and manage simulation workloads to meet project deadlines.
• Establish and enforce best practices, standards, and processes for simulation activities.

• Technical Responsibilities

• Oversee and review FEA simulations for static, dynamic, thermal, NVH, drop/impact, or fatigue analysis (as applicable to the industry).
• Guide the team in developing accurate CAE models and validating results through correlation with physical tests.
• Approve modelling approaches, boundary conditions, and meshing strategies to ensure reliable results.
• Drive design optimization through iterative simulation and data-driven recommendations.
• Support root cause analysis of product failures and develop corrective measures.

• Cross-functional Collaboration

• Work closely with design, testing, and manufacturing teams to integrate analysis insights early in the product development cycle.
• Communicate technical findings and design recommendations to stakeholders in a clear, actionable format.
• Participate in design reviews and project planning meetings.

• Continuous Improvement

• Stay updated with the latest CAE tools, simulation techniques, and industry standards.
• Promote automation, process efficiency, and digital transformation in simulation workflows.
• Provide training and technical guidance to upskill the FEA team.

Qualifications

• Education:

• Bachelor’s and master’s degree in mechanical, Aerospace, or Automotive Engineering with reputed institutions such as IITs or NITs.

• Experience:

• 10–15 years of experience in FEA / CAE with at least 3–5 years in a leadership or managerial role.
• Proven experience in leading complex analysis projects for structural, thermal, or dynamic behavior.

• Technical Skills:

§ Proficiency in tools such as ANSYS, Altair, NASTRAN, LS-DYNA, or similar.

§ Must have expertise on Linear, Non-Linear, Modal and Vibration Analysis using ANSYS Software.

§ Strong understanding of material modelling, non-linear analysis, and optimization techniques.

§ Deep understanding of contacts & material non-linearities and ability to debug convergence issues.

§ Expert in ability to interpret the FEA results and predict the root cause of failure.

§ Validate concept designs using simulation techniques and determine design robustness, critical to function requirements.

§ Capable of handling multiple projects simultaneously.

§ Provides technical leadership & coaching to the team to execute projects and recommend/make key engineering decisions.

§ Deploy standardized process and work methodologies.

§ Work with engineering team of different line of business for simulation need and recommend design changes as applicable.

§ Experience in understanding top level functional requirement of a product.

§ Familiarity with CAD tools (Creo, NX, SolidWorks) and PLM systems is desirable.

§ Knowledge of scripting (Python, MATLAB) for process automation is a plus.

§ Strong conceptual, problem solving and analytical skills.

§ Must be fluent in English with excellent communication skills.

§ Ability to prepare comprehensive technical reports, crisp presentations, proposals, statements of work etc.

§ Good experience with MS Office tools (Excel, Word, PowerPoint).

§ Candidate must be a self-starter with a positive attitude, high ethics, and a track record of working successfully under pressure in a time-constrained environment.

Performance Indicators

·        Accuracy and reliability of analysis deliverables.

·        Timely delivery of simulation reports supporting design milestones.

·        Reduction in physical prototype iterations through predictive analysis.

·        Team competency development and resource utilization efficiency.