Key skill requirements:
Supply Chain Master Data
Strong understanding of Material/Product, Customer, Vendor/Supplier, Plant, BOM, UOM, sourcing/procurement, and reference data.
Hands-on knowledge of SAP master data, data dependencies, validation rules, and downstream business impact.
Ability to translate business requirements into Critical Data Elements (CDEs), data quality rules, validation logic, and remediation workflows.
Data Quality Expertise
- Experience in data profiling, analysis, and identifying patterns across different portfolios.
- Ability to design preventive and detective data quality controls and dashboards.
- Experience automating recurring data quality checks and rule frameworks.
- Understanding of DQ scorecards, issue management, root-cause analysis, and remediation.
AI and Agentic AI Capabilities (Key Differentiator)
- Hands-on experience with LLMs, RAG/GraphRAG, and tool/function calling.
- Experience building AI agents, multi-agent orchestration, and agent-to-system/tool integration.
- Strong Python, SQL, and API-based development skills.
- Experience with platforms/frameworks such as Azure OpenAI and Microsoft Copilot Studio.
- Ability to build AI agents that can profile data, detect and analyze anomalies, propose DQ rules, explain failures, and recommend remediation, with appropriate human approval controls.