CWM Data Analyst

General Mills, a renowned global food company, is seeking a motivated Data Analyst to join its Contingent Workforce Management (CWM) Program within the Global Shared Services (GSS) function at its India Global Shared Services Centre in Powai, Mumbai. This role is crucial for ensuring the efficient and effective management of the company's global contingent workforce.

The GSS function at General Mills is dedicated to driving service excellence and cost-efficiency across various enterprise functions, including Employee Services, Business Services, Global Workforce Solutions, and Global Data Governance Services. As a Data Analyst within the CWM Program, you will be instrumental in supporting the global expansion and standardization of contingent workforce processes.

Key responsibilities include collecting, validating, and ensuring the integrity of contingent worker data within the Workday VNDLY Vendor Management System (VMS). You will prepare data for bulk uploads, conduct regular data audits and reconciliations, and provide support to VMS users. This role also involves actively participating in strategic projects focused on program enhancement, system integrations, and policy development. You will collaborate with cross-functional teams, assist in developing training materials, and support change management efforts. The role may also provide backup support during peak periods of requisition management and contribute to reporting and analytics to drive strategic decision-making.

This is a hybrid role, requiring a commitment to working from the Powai, Mumbai office during specified shift timings (1:30 PM to 10:30 PM IST). The ideal candidate will possess strong analytical skills, meticulous attention to detail, and a proactive approach to problem-solving in a dynamic global environment. A Bachelor's degree in a related field and a minimum of 2 years of experience in data analysis, HR operations, or contingent workforce management are preferred, along with proficiency in Microsoft Excel and experience with VMS, particularly Workday VNDLY.