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.
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
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