Project Lead - Process Optimization

Looking for challenging role If you really want to make a difference - make it with us

Siemens Gas and Power (GP) is a global pacesetter in energy, helping customers to meet the evolving demands of today's industries and societies. GP comprises broad competencies across the entire energy value chain and offers a uniquely comprehensive portfolio for utilities, independent power producers, transmission system operators and the oil and gas industry. Products, solutions and services address the extraction, processing and the transport of oil and gas as well as power generation in central and distributed thermal power plants and power transmission in grids. With global headquarters in Houston in the U.S. and more than 64,000 employees in over 80 countries, Siemens Gas and Power has a presence across the globe and is a leading innovator for the energy systems of today and tomorrow, as it has been for more than 150 years.

Your new role – challenging and future-oriented

• You would be project lead for the process optimization projects for thermal power plants.
• As part of your responsibility, you would be engineering & commissioning of process optimization solutions up to customer expectations & satisfaction.
• Your profile requires travelling to many project sites for customer interactions and final commissioning of process optimization solutions.

We don't need superheroes, just super minds

We've got quite a lot to offer. How about you

This role is based in Gurgaon, where you'll get the chance to work with teams impacting entire cities, countries – and the shape of things to come.

We're Siemens. A collection of over 379,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit and business need. Bring your curiosity and imagination and help us shape tomorrow.

Skills Required

System Modelling