Join Deloitte as a Lead Senior Associate in Engineering Foundry & Managed Services, focusing on iPPE & Automotive PPDS. This role is based in Hyderabad and offers an opportunity to work with cutting-edge leaders and organizations shaping the future.

At Deloitte, we encourage you to bring your whole self to work. We provide a dynamic environment for collaboration, innovation, growth, and impactful contributions. Our purpose is to drive positive change for clients, our people, and society.

This position is integral to our Engineering as a Service offering, contributing to India's growing impact on the global economy. You will be part of a team dedicated to unleashing potential and realizing opportunities.

Design, configure, and implement SAP iPPE models, including Product Structure, Process Structure, and Factory Layout for automotive manufacturing. Develop and maintain these models to accurately reflect product and process engineering needs.

Configure and manage Variant Configuration (VC/AVC) for products with numerous variants, maintaining critical master data like Production Versions, PDS, Routing, and BOMs. Generate Production Data Structures (PDS) from iPPE models, handling time-dependent process parameters (TDPP) and product structures.

Implement model mix planning, takt-based planning, and Rapid Planning Matrix (RPM) processes. Apply finite scheduling, manage bottleneck resources, and optimize sequence-dependent setup activities. Handle CIF error management, support integration with EWM, and manage master data migration.

Support Engineering Change Management using iPPE models. Collaborate closely with business stakeholders to assess business models and manufacturing processes. Resolve issues related to material master, BOMs, routings, and production orders within automotive contexts.

We are seeking candidates with demonstrated expertise in SAP APO-PPDS or SAP S/4HANA Manufacturing (PP/DS), with a strong emphasis on SAP iPPE. A solid background in discrete and repetitive manufacturing environments is essential, along with experience in Variant Configuration and automotive industry processes.

Proven capability in developing iPPE models, working with Product Structure, Process Structure, and Factory Layout is required. Proficiency in generating and managing Production Data Structures (PDS), including TDPP and related configurations, is also necessary.

Candidates should possess experience with model mix planning, takt-based planning, and Rapid Planning Matrix (RPM). Hands-on experience with CIF error handling, EWM integration, and master data migration is crucial. Familiarity with Engineering Change Management processes using iPPE models is expected.

Automotive industry experience, including addressing operational and configuration-related challenges, is highly valued. A Bachelor's or Master's degree in Computer Science or a related field, or equivalent work experience, is desired. The role requires 7-9 years of relevant business experience.