Lead Engineer Should Process ToolsMethods

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: 20 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Description Summary

Come and join our powerful unified force with the energy to change the world.

Gas Power business needs parts that are cost-competitive and on time. We provide the data to make that happen. Our team develops rigorous should-cost models for bought-out components in combined-cycle plants and digital tools that estimate both manufacturing cost and cycle time with high fidelity. With that transparency we identify gaps between quotes and true cost enable fact-based negotiations for deflation and partner with suppliers and internal shops to address delivery and capacity constraints. The Should Cost digital team develops these tools inhouse addressing the emerging needs of Supply Chain.

In this role you will be owning a set of Should Cost/ process tools (Gas Power Digital Factory; ACE Raw Material Demand Estimator etc..) demonstrate project leadership skills to achieve on time this role you will be working closely with Should Cost team P2V Sourcing and Mfg teams to align tool development charter with biz priorities. As the project leader for Cost tools you will be responsible for on-time delivery of releases automation AI integration and user-experience addition the role also gives scope to innovate on building new digital tools & methods for should process application across SQDC & Sustainability pillars.

Job Description

Essential Responsibilities

Drive innovation to enhance existing Should process digital tools lead them through implementation.

Demonstrate ownership of Strategic Should Cost tools build roadmap to enhance tool outcomes & user adoption. Translate the long-term tool roadmap into quarterly monthly and weekly deliverables for the team.

Contribute Act as the operational lead forte Gas Power Digital Factory development program with FTY 1

Understand finance concepts that impact how cost is calculated and reported. Labor rates Handling rates Profit & SG&A escalation Unit cost reported etc.

Establish strong partnerships with digital & infrastructures teams to build enterprise level system for should process.

Partner with Gas Power Digital teams to drive AI integration with in Should Process tools portfolio.

Identify AI use cases for Should Cost/Process tools to drive implementation.

Drive adoption of agile and lean tools during development and deployment process.

Partner with supply chain Should Cost P2V AME & Design teams discuss any new manufacturing methods that need to be captured for cost understand cost drivers with new technology concepts. Help design iterate for lowest cost based on supply chain & user feedback.

Work closely with GP Should Cost team to provide support on new costing methods implementation & adoption

Qualifications / Requirements

Bachelors or Masters degree in Mechanical/ Manufacturing/ Production Engineering from an accredited university or college

Minimum 3-5 years of experience in working with aPriori CMWB module or any other engineering tools. Exposure to aPriori deployment and infrastructure aPriori cost insights is a plus

Demonstrated expertise on python jupytr and other big data analytics platforms

Passionate towards learning costing manufacturing methods & coding

Ability to connect with stakeholders from diverse domains and provide technical leadership for high performing teams in a competitive and time sensitive environment

Ability to work in a cross-functional environment

Ability to learn new skills & deliver while learning

Desired Characteristics

Experience in developing physics based cost tools aPriori VPE customization and CSL coding

Strong oral and written communication skills

Strong interpersonal and leadership skills

Additional Information

Relocation Assistance Provided: Yes

Required Experience:

Job Description SummaryCome and join our powerful unified force with the energy to change the world.Gas Power business needs parts that are cost-competitive and on time. We provide the data to make that happen. Our team develops rigorous should-cost models for bought-out components in combined-cycle...