Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.
YASH Technologies is hiring SAP EWM professionals with 6-8 years of in-depth SAP EWM experience. The role requires a Bachelor’s degree in CS or equivalent and readiness to travel for 2 weeks onsite to Italy/Switzerland for knowledge transfer.
Experience with SAP S/4HANA Rise on AWS is mandatory, with S4 certification as an advantage. Responsibilities include handling WM structures, master data, inbound/outbound processing, and production integration.
YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation.
At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.
Should have a minimum of 6-8 years of in-depth knowledge of the SAP EWM module.
Bachelor’s degree in computer science or equivalent from an accredited college or university.
Consultant should be travel ready for 2 weeks onsite - Country Italy / Switzerland for knowledge transfer.
Experience of SAP S/4 HANA Rise on AWS is mandatory.
S4 Certification will be added advantage.
Experience on the following topics in EWM module
Must be proficient in handling Issues/ troubleshooting / support functions.
Should have experience in building the integration of SAP with applications which are non-SAP.
Good knowledge on ticketing tools like service now, solution Manager etc.
Ability to establish and maintain a high level of customer trust and confidence.
Excellent communication skills.
Ready to work in 24 x 5 support environment.
At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.