Join Deloitte's Engineering Foundry & Managed Services team in Hyderabad as a Lead Senior Associate, specializing in Engineering as a Service. This is an exceptional opportunity to contribute to India's growing impact on the global economy, working alongside innovative leaders and shaping the future of technology.

At Deloitte, we encourage you to bring your whole self to work, fostering a collaborative and purpose-driven environment. This is your playground to innovate, grow, and make a significant impact.

This role focuses on iPPE & Automotive PPDS, demanding expertise in designing, configuring, and implementing SAP iPPE models for automotive manufacturing. You will develop and maintain these models, ensuring accurate product and process engineering representation.

Key responsibilities include configuring Variant Configuration (VC/AVC) for products with multiple variants, maintaining master data like Production Versions, PDS, Routing, and BOMs. You will generate Production Data Structures (PDS) from iPPE models, manage time-dependent process parameters (TDPP), and product structures.

The role also involves implementing and supporting model mix planning, takt-based planning, and Rapid Planning Matrix (RPM) processes. You will apply finite scheduling techniques, manage bottleneck resources, and optimize sequence-dependent setup activities.

Additionally, you will handle CIF error management, support integration with EWM, and manage master data migration. Supporting the implementation of Engineering Change Management using iPPE models and collaborating with business stakeholders to evaluate manufacturing processes are crucial. You will also assist in resolving issues related to material master, BOMs, routings, and production orders in automotive contexts.

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

Proven ability in developing iPPE models, managing Production Data Structures (PDS) including TDPP, and hands-on experience with CIF error handling, EWM integration, and master data migration are required. Familiarity with Engineering Change Management processes via iPPE models and direct automotive industry experience are key.

Desired qualifications include a Bachelor's or Master's degree in Computer Science or a related field, or equivalent work experience, along with 7-9 years of relevant professional experience. Experience working closely with business stakeholders on manufacturing process evaluation is also highly valued.