Data Management Specialist Nestle

Main Purpose of the Job

The primary responsibility of the Data Operations Associate is to maintain high standards of data quality throughout all stages of collection and processing. This involves working closely with internal teams and external partners to guarantee that data is accurate, validated, and transformed according to Nestl s reporting standards.

Key Responsibilities

• Analyze data to identify trends, insights, and anomalies.
• Perform data cleansing, transformation, and validation, including management of SKU-level datasets.
• Ensure strict adherence to data review guidelines and process maps.
• Research opportunities to leverage big data and propose enhancements to data processes.
• Present analytical findings to markets and leadership teams.
• Collaborate with cross-functional teams such as Supply Chain, Procurement, F&C, Sales Support, and Decision Support.
• Manage relationships with retailers and distributors to collect accurate sell-out data.
• Transform incoming data formats to align with Nestl reporting requirements.
• Update SharePoint repositories with refreshed data and documentation.
• Support the refresh cycles of Power BI dashboards and manage data ingestion pipelines.
• Execute SKU cleansing and data validation workflows using Power Apps.
• Assist with customer data integration and cleansing projects.
• Operate internal data management systems and perform trend analysis.
• Ensure the secure handling of confidential data and comply with Nestl policies.
• Meet deadlines and deliver accurate, validated outputs in accordance with Service Level Agreements (SLAs).

Key Performance Indicators (KPIs)

• Maintain a Data Accuracy Rate of at least 98% across all deliverables.
• Achieve an on-time data delivery adherence rate of at least 95%.
• Identify and resolve data issues within established SLAs.
• Ensure the success rate and timeliness of Power BI dashboard refreshes.
• Comply with SharePoint update requirements and maintain complete documentation.
• Complete SKU cleansing cycles within the targeted timeframe.
• Receive high market and stakeholder satisfaction scores for data quality and communication.

Success Measures

• Consistent delivery, validation, and transformation of data from retailers and distributors, with no escalations.
• SKU master data remains fully updated and discrepancies are minimized.
• Power BI dashboards display accurate, current, and decision-ready data.
• Stakeholders recognize the associate as reliable, analytical, and attentive to detail.
• Cross-functional collaboration leads to improved efficiency and reduced data-related risks.
• All processes adhere strictly to Nestl data governance, confidentiality, and quality standards.