NON-CONFIDENTIAL

B2B GET Senior Data Analyst

Migration, Finance & Master Data — BT356 GET (SAP)

1. Role Purpose

The Senior Data Analyst leads analysis activities supporting the migration and integration of data into the B2B GET target landscape (SAP S/4HANA). The role bridges business process and technical implementation, translating confirmed GET data migration requirements (SG-P022) into local B2B delivery requirements across the ESUK B2B data landscape.

The role is accountable for source system analysis, source-to-target mapping, data quality definition, and reconciliation design across a multi-source estate. Given the reliance on Finance data and Enterprise Utility Applications (EUAs), the role must combine strong utility-domain knowledge with S/4HANA target understanding, while remaining mindful of adjacent Master Data Management (MDM) and reporting activities that depend on the same data.

2. Key Responsibilities

Data Discovery & Analysis

• Analyse source data structures across B2B applications and End User Applications (EUAs)
• Profile source systems, identify data ownership and stewardship, and document AS-IS and TO-BE data flows.
• Conduct impact assessments spanning migration, integration, MDM and reporting.
• Identify duplicate, obsolete, redundant and orphaned records ahead of migration.

Data Mapping & Transformation

• Produce and version-control source-to-target mapping (STTM) specifications with field-level lineage and business transformation rules.
• Define transformation logic and resolve mapping conflicts with Data Architects and Finance SMEs.
• Support canonical and target data model definition, ensuring traceability from requirement to delivery.
• Ensure mapping decisions are reviewed, approved and formally signed off by data owners.

Finance Data & EUAs (Crucial)

• Lead analysis of Finance datasets — customer/vendor business partners, contracts, billing, revenue, AR/AP open items, ledger interfaces, cost objects (CC/PC/WBS) and settlement.
• Work across B2B Key Systems and EUA sources
• Define reconciliation controls (row counts, checksums, business-rule checks) proving parity between source and target.
• Produce migration evidence packs and support Finance workstream sign-off (Transactions, Accounting, Controlling, Treasury, Tax).

Master Data Management (MDM)

• Support MDM strategy, master data ownership and stewardship definition.
• Support golden-record definition and de-duplication rules across sources.
• Assist establishment of ongoing governance and data quality controls beyond go-live.

Reporting & Analytics

• Assess downstream reporting impacts and dependencies (operational, regulatory and MI).
• Support Power BI / SAP Analytics Cloud reporting requirements and reporting reconciliation.
• Ensure migrated data sustains reporting continuity through and beyond cutover.

Testing, Validation & Governance

• Define migration test scenarios; support SIT, UAT and dress-rehearsal cycles.
• Manage data defects through resolution; validate completeness, accuracy and integrity.
• Maintain migration RAIDDA items and support SteerCo reporting and formal sign-off gates.

3. Skills & Experience

Essential

• Proven experience delivering data migration / integration analysis on enterprise ERP transformation programmes.
• Crucial: strong hands-on experience of analysing complex End User Applications (EUAs) and Finance data (billing, AR/AP, GL, settlement, contracts).
• Expert source-to-target mapping and transformation design.
• Strong SQL for profiling, analysis, validation and reconciliation.
• Experience of migration reconciliation, audit evidence and business sign-off.
• Exposure to Master Data Management and reporting/MI dependencies.
• Strong stakeholder engagement and clear technical documentation skills.
• Experience of programme delivery frameworks.

Highly Desirable

• Experience of SAP S/4HANA as a migration target platform.
• Energy or utilities sector experience; SAP IS-U / SAP MDG exposure.
• Power BI / SAP Analytics Cloud reporting knowledge.
• Data governance and GDPR awareness in a migration context.
• Azure data platform familiarity; Python or scripting for data automation.
• Jira / Confluence for tracking and collaboration.

4. Success Measures

• Migration mappings signed off to schedule with full traceability.
• Data quality and reconciliation acceptance criteria achieved.
• Finance and EUA reconciliation sign-off secured.
• Successful dress-rehearsal outcomes; no critical data defects at go-live.
• Reporting continuity and MDM controls demonstrably maintained.