Data Migration Lead - (SAP S/4HANA)
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United States · Prague, Czechia · Czechia · Riverview, FL, USA
Job Description
Data Migration Lead – SAP S/4HANA (R4)
Location: Prague, Czech Republic (Global IT Hub)
Within Animal Health IT - Enterprise Process Management (EPM) PMO/Integration & Data Management we have the Data Migration Lead – (SAP S/4HANA) role
Role summary
- Lead the design and execution of selective data transfers(SDT) into SAP S/4HANA using SAP DMLT (Data Migration & Landscape Transformation) solutions. Responsible for data strategy, extraction/mapping/transformation, quality & reconciliation, and coordination with SAP technical teams, business data owners, and project managers to ensure timely, auditable, and business-accepted data cutover.
Core responsibilities
- Define the selective data transfer scope, approach, timeline, and cutover strategy in collaboration with program leads and business stakeholders.
- Oversee mass data extraction, cleansing, staging, and targeted imports using DMLT and related ETL tools.
Experience:
- Hands-on experience leading SAP S/4 selective data transfer initiatives using SAP DMLT or SAP Landscape Transformation (SLT) / Migration Cockpit - required
- 5+ years overall SAP data migration experience, with at least 3–5 years specifically on S/4HANA migrations required
- Understanding of S/4 data model changes (universal journal, new master data structures, and document model differences) across Finance, Logistics, and relevant modules. required
- Ability to structure data, planning, milestones and day-to-day activities required
- Strong stakeholder management in a matrix, international environment (EU, APAC, NA) preferred
- Experience in regulated industries (Life Sciences / Pharma) preferred
R4 Capability Alignment
- Primary: R4 Data
- Secondary: R4 Deployment & Cutover, R4 Quality & Validation
- Influencing: R4 Solution Design, R4 Program Governance
Role Impact
- Ensures data readiness and integrity for S/4HANA go‑live
- Reduces operational-, compliance-, and regulatory risk
- Enables successful global adoption of the R4 platform
What we offer:
Exciting work in a great team, global projects, international environment
Opportunity to learn and grow professionally within the company globally
Hybrid working model, flexible role pattern
Pension and health insurance contributions
Internal reward system plus referral program
5 weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements annually, 40 paid hours annually for volunteering activities, 12 weeks of parental contribution
Cafeteria for tax free benefits according to your choice (meal vouchers, sport, culture, health, travel, etc.), Multisport Card
Vodafone, Raiffeisen Bank, Foodora, and other discount programs
Up-to-date laptop and iPhone
Parking in the garage for drivers or showers for bikers
Competitive salary, incentive pay, and many more
Required Skills:
Business Data Analytics, Business Information Systems, Business Intelligence (BI), Data Engineering, Data Management, Data Migrations, Data Modeling, Data Strategies, ETL Tools, Logistics, Logistics Management, Quality Management, SAP Data Migration, SAP Landscape, SAP Technical SupportPreferred Skills:
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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
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RegularRelocation:
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Job Posting End Date:
05/30/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.