About the Company
We are a premier global enterprise solutions and HR technology transformation partner working alongside hyper-scale multinational corporations, complex joint ventures, and global enterprise clusters. By combining advanced master data governance, predictive data modeling, and cutting-edge cloud architecture, we build secure and cohesive digital ecosystems that power intelligent HR operations. We focus on structural data integrity, cross-border data privacy engineering, and cultivating top-tier senior technical advisory talent in Singapore.
About the Job
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.
Your mission goes far beyond basic technical ETL (Extract, Transform, Load) execution. You must possess a deep functional command of how HR data behaves inside the SuccessFactors Employee Central engine. You will orchestrate complex multi-cycle data migrations, enforce regional data privacy standards (including GDPR and PDPA), and meticulously build a clean, trusted, and harmonized master data foundation engineered to support advanced human capital analytics and emerging GenAI/agentic frameworks.
Key Responsibilities
HR Data Strategy, Target-State Architecture & Harmonization
Target-State Modeling: 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.
Global Harmonization: Drive multi-instance data harmonization across global clusters, ensuring complete data consistency across Foundation Objects (business units, cost centers, job frameworks, pay structures), custom fields, and picklist values.
Multi-Entity Calibration: Design a unified global master data framework that seamlessly accommodates regional legal entity nuances, joint venture structures, and cross-cluster reporting analytics frameworks.
End-to-End Data Migration & Cleansing
Migration Orchestration: Blueprint, sequence, and execute large-scale data migration cycles (including initial profiling, mock data runs, differential delta mapping, reconciliation, and production cutovers) using specialized tools such as Spinifex, OpenText, or cloud ETL platforms.
Data Integrity Gates: Formulate comprehensive mapping rules, structural transformation logic, automated validation scripts, and custom Excel data manipulation routines to bridge legacy data stores with SuccessFactors.
Source-Level Remediation: 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.
AI Readiness Hardening: Enforce strict data profiling thresholds to guarantee that processed employee records achieve the structural data maturity required for secure GenAI and agentic workflows.
Data Governance, Compliance & Integration Design
Policy Enforcement: Establish and lead global data governance forums, defining clear data ownership boundaries, data steward accountabilities, centralized data dictionaries, and corporate business glossaries.
Data Privacy Engineering: 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.
Integration Data Contracts: 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 (such as non-SAP HR payroll engines, corporate finance ledgers, and ITSM/ServiceNow configuration databases).
Team Leadership & Value Realization
Workstream Leadership: Lead, mentor, and coordinate a cross-functional team of data analysts, migration developers, and data stewards across onshore (Singapore) and offshore execution hubs.
Value Tracking: 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.
Skills & Experience Required
Must-Have Skills (Mandatory for Skills Matching)
SuccessFactors Data Mastery: 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.
Employee Central Data Model Expertise: Deep functional, hands-on command of the SuccessFactors Employee Central (EC) data structure, including Foundation Objects, Position Management mechanics, and complex employment record schemas.
Global Migration Lifecycle Execution: Proven experience leading the data track for massive, multi-instance global HR transformation programs, managing automated ETL cycles from legacy landscapes into SuccessFactors.
Specialized HR Tooling: Practical experience with dedicated HR migration and profiling utilities (e.g., Spinifex, OpenText) or expert-level data manipulation scripting capabilities.
Data Privacy & Compliance Governance: Demonstrable knowledge of implementing data privacy controls, access masking, and cross-border routing rules in compliance with GDPR and PDPA mandates.
Good-to-Have Skills (Preferred Differentiators)
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.
Qualifications
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.
