Senior Manager SAP S/4HANA Data Conversion & Migration (Non-SAP to SAP)

Xylem is a Fortune 500 global water solutions company dedicated to advancing sustainable impact and empowering the people who make water work every day. As a leading water technology company with 23,000 employees operating in over 150 countries, Xylem is at the forefront of addressing the world's most critical water challenges. We invite passionate individuals to join our team, dedicated to exceeding customer expectations through innovative and sustainable solutions.

This role leads one of the highest-risk components of ERP transformation by ensuring accurate migration of legacy data into SAP S/4HANA. The position establishes migration strategies, data cleansing processes, validation controls, reconciliation procedures, and cutover readiness plans. High-quality migration directly impacts business continuity, user adoption, and post-go-live operational stability. The role protects the digital core by ensuring that critical business data is complete, accurate, and fit for future operations. Successful data migration is a foundational requirement for realizing value from the ERP transformation investment.

Key Responsibilities

Conversion strategy and execution

• Own the end-to-end data conversion strategy: scope, object inventory, source-system profiling, extraction
  
  

approach, transformation rules, load sequencing, and validation design.

• Lead legacy data discovery across non-SAP ERPs where documentation is thin and business logic is
  
  

undocumented, reverse-engineering meaning from the data itself rather than relying on legacy system owners

alone.

• Design and operate the migration factory — reusable templates, mappings, rule libraries, and automation —
  
  

so each wave costs less and runs cleaner than the last.

• Own mock conversion cycles end to end, with defined defect thresholds and reconciliation criteria as formal
  
  

gates into cutover.

• Plan and execute production cutover loads, including timing, dependencies, fallback, and post-load
  
  

reconciliation.

Data quality and readiness

• Establish measurable data quality standards with business-owned acceptance criteria per object, and report
  
  

readiness as a number, not a status color.

• Build proactive cleansing programs in the legacy environment ahead of extraction, with business data owners
  
  

accountable for remediation.

• Instrument profiling, validation, and reconciliation so quality issues surface during mock cycles rather than
  
  

during hypercare.

• Own post go-live data defect root cause analysis and drive fixes into the template and the factory, not just into
  
  

the affected instance

Master data governance

• Partner with the MDG lead to ensure converted data enters a governed steady state — ownership,
  
  

stewardship, workflow, and rules that prevent immediate re-degradation.

• Define the sustaining operating model for master data across segments after each wave closes.
  
  

Leadership and stakeholder management

• Lead a team of data leads, ETL developers, functional data analysts, and partner resources across onshore
  
  

and offshore.

• Hold system integrator and AMS partners accountable for conversion quality, staffing continuity, and delivery
  
  

commitments.

• Communicate data readiness credibly to program and segment leadership, including when the honest answer
  
  

is that a wave is not ready.

Qualifications Required

• 12–15+ years in enterprise data migration, with at least 8 years focused on SAP conversion and 5+ years leading teams.
• Proven delivery of multiple full-cycle non-SAP to S/4HANA conversions at global scale — heterogeneous
  
  

legacy sources, multi-country, multi-wave. Greenfield or selective transition experience specifically; system

conversion experience alone is not sufficient.

• Deep hands-on command of SAP Migration Cockpit (staging tables and LTMOM), SAP Data Services / BODS,
  
  

and at least one enterprise migration platform such as Syniti ADM, BackOffice, or equivalent.

• Strong SQL and scripting (Python or equivalent) — able to profile and interrogate source data personally, not only direct others to do it.
• Deep functional data knowledge across core objects: material master, BOM and routing, customer and vendor,
  
  

pricing, open orders, inventory, fixed assets, open AR and AP, and GL balances.

• Demonstrated ownership of data quality frameworks with business-facing metrics and formal acceptance gates.
• Experience with SAP MDG or a comparable master data governance platform.
• Track record of recovering or hardening a migration that was previously failing — this is a specific and deliberate requirement.
  
  

Preferred

• RISE with SAP experience; familiarity with SAP Datasphere, Cloud ALM, and BTP-based data services.
• Signavio or comparable process mining used to inform conversion scope and rules.
• Manufacturing, industrial, or engineered-products data complexity (configurable products, service parts, long-lived installed base).
• Experience building a conversion capability subsequently reused for acquisition integration.
  
  

Success in the First 12 Months

A defensible object inventory and readiness baseline across in-scope legacy systems. Mock cycles that produce

declining defect curves against published thresholds. Cutover loads executed with reconciled, business-signed-off

results. A documented, reusable conversion factory. And a measurable reduction in data-attributed defects in hypercare compared with prior waves.

Operating Principles You Will Work Under

• Products, not projects. Persistent teams aligned to value streams, funded by capacity rather than project
  
  

cycles, each paired with a business process owner accountable for the outcome.

• Clean core is non-negotiable. Extensions live on BTP, the core stays standard, and custom code is
  
  

governed at the point of creation.

• Paved road, not toll booth. Golden paths, reference architectures, and reusable patterns, with guardrails
  
  

enforced in the pipeline rather than in a design authority meeting.

• Compliance by default. Controls are designed into the platform and evidenced automatically, so control
  
  

integrity holds at deployment scale.

• Accountable for value, not volume. Success is measured in business process KPIs, adoption, and realized
  
  

value, not tickets closed or hours delivered.

• Intelligent enterprise by design. AI and agent enablement, and the data readiness that makes both credible,
  
  

are owned capabilities.

• Global template authority, local execution. Template integrity is held centrally through the current
  
  

deployment horizon, with a defined path to greater product-team autonomy.

Join the global Xylem team to be a part of innovative technology solutions transforming water usage, conservation, and re-use. Our products impact public utilities, industrial sectors, residential areas, and commercial buildings, with a commitment to providing smart metering, network technologies, and advanced analytics for water, electric, and gas utilities. Partner with us in creating a world where water challenges are met with ingenuity and dedication; where we recognize the power of inclusion and belonging in driving innovation and allowing us to compete more effectively around the world.