Master Data Lead

The Master Data Lead is the single point of accountability for ensuring that all master data required for SIT, UAT, cutover, and post-go‑live operations is accurate, complete, validated, and business‑ready. The role acts as the bridge between project teams, business units, data champions, and technical MDM/MDG teams, ensuring that master data does not become a blocker to testing, deployment, or operational continuity.

The Master Data Lead ensures that all master data objects (customer, vendor, material, finance objects, org structures, WBS, bank data, profit center, etc) are prepared, governed, and validated across SIT Cycle 2, UAT, and go‑live. They coordinate with BU teams to manage data readiness, resolve defects, drive cleansing and enrichment, and ensure that test cycles run with production‑grade data. During cutover and post‑go‑live, they safeguard business continuity by overseeing data loads, validating migrated data, and supporting hypercare to stabilise operations.

Key Responsibilities

Ensure all master data required for SIT scenarios is created, extended, and validated.

• Coordinate defect resolution for data‑related issues.
• Work with process leads to ensure test scripts reflect realistic master data conditions.
• Maintain a controlled backlog of data gaps and remediation actions.

During UAT

• Lead BU data champions to validate master data in UAT environments.
• Ensure master data are fully aligned to business scenarios.
• Support end‑to‑end scenario execution by ensuring cross‑tower data consistency.
• Sign off on master data readiness for cutover.

During Cutover & Go‑Live

• Oversee master data migration, load sequencing, and reconciliation.
• Validate completeness and accuracy of migrated data before go‑live.
• Ensure business units have the correct data to operate from Day 1.
• Manage hypercare triage for data defects impacting operations.

Post Go‑Live (Stabilisation)

• Monitor data quality KPIs and resolve defects rapidly.
• Support business units in stabilising processes dependent on master data.
• Drive continuous improvement and governance adoption.
• Transition responsibilities to BAU MDM teams.