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We are seeking an experienced, elite-level SuccessFactors Data Lead to take complete strategic ownership of the end-to-end data strategy, architecture, and migration delivery across a complex multi-instance global enterprise. In this high-impact position, you will design the data models, master data governance rules, and quality thresholds across multiple SAP SuccessFactors instances, legacy platforms, and fragmented HR tools.
Job Responsibility
Define and own the enterprise HR data strategy across multiple SuccessFactors instances and legacy platforms, crafting target-state data schemas, position hierarchies, corporate taxonomies, and strict master data standards
Drive multi-instance data harmonization across global clusters, ensuring complete data consistency across Foundation Objects, custom fields, and picklist values
Design a unified global master data framework that seamlessly accommodates regional legal entity nuances, joint venture structures, and cross-cluster reporting analytics frameworks
Blueprint, sequence, and execute large-scale data migration cycles using specialized tools such as Spinifex, OpenText, or cloud ETL platforms
Formulate comprehensive mapping rules, structural transformation logic, automated validation scripts, and custom Excel data manipulation routines to bridge legacy data stores with SuccessFactors
Design and deploy automated data quality profiling and deduplication frameworks, establishing clear data health KPIs and collaborating with regional business teams to correct anomalies at the source
Enforce strict data profiling thresholds to guarantee that processed employee records achieve the structural data maturity required for secure GenAI and agentic workflows
Establish and lead global data governance forums, defining clear data ownership boundaries, data steward accountabilities, centralized data dictionaries, and corporate business glossaries
Define, configure, and audit strict localized data privacy controls, cross-border data transfer rules, and data masking protocols within SuccessFactors data models to ensure absolute compliance with GDPR and PDPA laws during testing and migration
Partner tightly with the Integration & Reporting Lead to define structural data contracts, API payload definitions, and master data synchronization paths between Employee Central and downstream systems
Lead, mentor, and coordinate a cross-functional team of data analysts, migration developers, and data stewards across onshore and offshore execution hubs
Establish value tracking metrics to measure data normalization successes, focusing on the reduction of manual reconciliation hours and the optimization of manager self-service data experiences
Requirements
Minimum 8+ years of hands-on HR technology experience with expert-level proficiency in HR data architecture, schema mapping, and master data management within the SAP SuccessFactors ecosystem
Deep functional, hands-on command of the SuccessFactors Employee Central (EC) data structure, including Foundation Objects, Position Management mechanics, and complex employment record schemas
Proven experience leading the data track for massive, multi-instance global HR transformation programs, managing automated ETL cycles from legacy landscapes into SuccessFactors
Practical experience with dedicated HR migration and profiling utilities (e.g., Spinifex, OpenText) or expert-level data manipulation scripting capabilities
Demonstrable knowledge of implementing data privacy controls, access masking, and cross-border routing rules in compliance with GDPR and PDPA mandates
Bachelor’s or Master’s degree in Computer Science, Data Architecture, Information Systems Management, Business Analytics, or a related technical/quantitative discipline
Outstanding consultative, workshop facilitation, and stakeholder management skills, with a proven ability to align competing priorities across global corporate divisions
Nice to have
Official SAP SuccessFactors certification (Employee Central module preferred)
Prior experience utilizing enterprise-grade master data management (MDM) platforms or automated data governance consoles
Familiarity with integration interface platforms (such as SAP Cloud Integration / CPI middleware) or downstream People Analytics reporting suites (Story Reports)
Deep comprehension of data maturity indexing required to feed downstream Large Language Models (LLMs) or autonomous agent networks