About the Organization:

Our client a global leader in data storage solutions, enabling organizations worldwide to manage and protect their data.

Job Details:

• Contract Duration: 12 Months

• Location: One North

• Working Days & Hours: Mon – Fri, 8am – 5.30pm

Role Summary

We are seeking for People & Places Data & Knowledge Operations Associates to provide hands-on, execution-focused support for data cleanup, content organization, validation, and AI readiness across core People & Places platforms. These roles focus on day-to-day delivery — ensuring that SAP SuccessFactors, SharePoint, and related systems contain data that is accurate, consistently structured, findable, and ready to support AI tools, automated workflows, and redesigned HR processes.

This is not an engineering, analytics, or system administration role. It is designed for someone who is detail-oriented, process-focused, and comfortable doing precise, methodical work directly in enterprise systems — following established standards and flagging issues clearly when they arise.

Key Responsibilities

1. Data Cleanup & Validation

• Perform routine data correction, normalization, and validation across People & Places datasets in SAP SuccessFactors and related platforms

• Identify and resolve missing, duplicate, inconsistent, or outdated records using established procedures

• Update fields, naming conventions, metadata, and controlled lists to maintain consistency standards

• Maintain audit trails and documentation for all changes made

2. Content Organization & Knowledge Management

• Organize People & Places content in SharePoint using approved structures, metadata schemas, and governance rules

• Tag, label, archive, and version documents so they are discoverable by AI tools and search

• Maintain policy, FAQ, and process documentation libraries to keep them current and AI-ready

• Support content migrations or reorganizations during workflow redesign efforts

3. Cross-System Data Consistency

• Support alignment of people data across SAP SuccessFactors, Gloat, Affinity, SharePoint, and related tools

• Identify and flag discrepancies between systems that impact reporting, workflows, or AI outputs

• Assist with data validation activities during migrations, integrations, or platform transitions

4. AI & Agent Readiness Support

• Prepare and validate datasets used by AI-enabled tools, agents, and workflows

• Follow checklists and quality standards for structuring content to improve AI performance (e.g., metadata, file naming, tagging conventions)

• Flag data risks that could impact AI accuracy, output reliability, or trust

• Support testing and validation of AI outputs by confirming underlying data accuracy and completeness

5. Workflow & Documentation Support

• Maintain simple trackers for data cleanup progress and issue resolution

• Assist with documenting data flows and source systems for HR and Workplace processes

• Help draft basic instructions, checklists, and knowledge articles as needed

• Partner closely with the Transformation BA and People Analytics team to prioritize and resolve data issues

Required Qualifications

• 1–3 years of experience in HR operations, data entry/maintenance, business administration, or similar roles

• Comfortable working directly in SAP, SharePoint, and Microsoft 365 tools (Teams, Excel, OneDrive)

• Strong attention to detail with a consistent habit of keeping data clean and organized

• Ability to follow structured processes and complete precise, repetitive work with high accuracy

• Good communication skills and willingness to ask questions when something is unclear

 Preferred Qualifications

• Experience supporting data cleanup, content structuring, or system transitions

• Familiarity with AI concepts, Microsoft Copilot, or enterprise search tools

• Understanding of metadata, file hygiene, or basic knowledge management practices

• Comfort learning new tools quickly in a fast-moving transformation environment

What Success Looks Like

People & Places data in SAP SuccessFactors and SharePoint is consistently accurate and well-organized

AI tools produce more reliable outputs because the underlying data is clean and accessible

Workflow redesign projects move faster because data issues are identified and resolved quickly

Teams find content easily — and trust what they find

Each associate becomes the go-to execution resource for data hygiene and content organization within their assigned platform or domain

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