Master Data Specialist — Finance Master And Costing

Job title: Master Data Specialist —Finance Master & Costing

The Opportunity: The Master data specialist will work on cleanup and sustainment for material valuation data (MBEW, EBEW, valuation classes), standard cost estimates, cost center and profit center master, G/L master, activity types, internal order master, and the costing variants that govern how value flows through the system

How You'll Make An Impact

• Execute finance master cleanup
• Personally execute valuation class consistency across MBEW and EBEW; reconcile valuation class assignments to G/L account determination (OBYC).
• Maintain G/L master (FS00, FSP0 / FSS0), cost center master (KS01 / 02 / 03), profit center master (KE51 / 52 / 53) including standard hierarchies (OKEON, KCH5N).
• Cleanse internal order master (KO01 / 02 / 03), activity types (KL13), and statistical key figures (KK01 / 02).
• Execute product costing cleanup
• Run standard cost estimates (CK11N for individual materials, CK40N for costing runs) on remediated material masters; release via CK24.
• Maintain activity prices (KP26) and ensure costing variant configuration (OKKN) is consistent with current operations.
• Reconcile cost component splits against expected margin structure; flag drift appropriately.
• Operate material price changes (MR21) where standard cost requires intervention outside the costing run cadence.
• Resolve cross-domain breaks end-to-end
• Diagnose when a finance defect originates upstream material master (valuation class, price control, standard cost), info records (PO price variance), vendor master (payment terms), customer master (terms of payment) and resolve at source.
• Pair with the Material Master Specialist on valuation class realignment; with Procurement & Info Records on price variance investigations; with Customer & Pricing on margin reporting drift.
• Close gates and sustain
• Operate Process Runner, Precisely Automate Studio, and MASS for high-volume finance master and costing data updates.
• Maintain the Defect Register for finance domain; feed coverage %, defect rate, and cycle-time inputs into the KPI Dashboard.
• Sign off Exit Gate Checklists at the three Definition of Done levels.
• Hand off sustainment patterns to BAU when a wave clears target DOD.
  
  

• Experience: 8+ years hands-on SAP master data execution with documented volume in finance domain — has personally maintained valuation classes, executed costing runs, and cleaned cost / profit center hierarchies at scale.
• End-to-end domain knowledge: Working understanding of how master data flows across all six domains and how finance data sits downstream of material, vendor, customer, pricing, and info records.
• Finance master depth: Fluent across MBEW, EBEW, SKAT / SKA1 / SKB1 (G/L), CSKS / CSKT (cost centers), CEPC / CEPCT (profit centers), AUFK (internal orders), valuation classes, account determination (OBYC, OBYK).
• Costing depth: Hands-on with costing variants (OKKN), cost component structures, standard cost estimate (CK11N, CK40N), cost release (CK24), activity prices (KP26), and material price changes (MR21).
• Transaction fluency: FS00, KS01 / 02 / 03, KE51 / 52 / 53, KO01 / 02 / 03, KL13, CK11N / CK24 / CK40N / CK13N, MR21, OKEON, OKKN, MASS, MDG_SW, SE16N — used daily.
• Mass maintenance tooling: Hands-on with Process Runner, Precisely Automate Studio, or LSMW.
• Investigation skill: Comfortable running working sessions with Controlling, Finance, Operations, and Engineering SMEs to trace finance master defects to their upstream sources.
• Bias to action: Energized by high-volume execution. Closes records, not tickets.
  
  

• Experience with COPA characteristic derivation and value field structures.
• Familiarity with parallel valuation, transfer pricing, or multiple ledger scenarios in S/4HANA.
• Exposure to S/4HANA Universal Journal (ACDOCA) and the unification of FI and CO.
• Background in industrial, capital equipment, or power generation finance operations.
• Experience in post-SI environments and remediation of go-live data debt at the finance layer.