Role: Data Governance SME Finance Technology
Location : New Brunswick, NJ
Duration: Contract to Hire
Job Description:
You will serve as the Data Governance Subject Matter Expert (SME) for the Finance Technology Group supporting the DS platform landscape, including SAP S/4HANA and the Data Hub. You will establish, maintain, and operationalize data governance standards across finance data domains—ensuring data quality, lineage, ownership, compliance, and consistent use across systems and analytics.
Key Responsibilities:
1. Data Governance Strategy & Operating Model
• Define and drive the governance approach for finance data across SAP S/4HANA and Data Hub
• Establish governance roles and workflows (e.g., data owners, stewards, custodians, approvers)
• Maintain governance charters, decision rights, escalation paths, and issue resolution processes
• Align governance practices to enterprise data management standards and compliance expectations
2. Data Ownership, Stewardship & Controls
• Facilitate data owner/steward onboarding and adoption for finance domains
• Ensure data stewardship activities are executed (definitions, review cycles, approval processes)
• Define approval and change management processes for key finance datasets and reference/master data
• Monitor adherence to governance standards and recommend corrective actions
3. Data Quality Management (DQ)
• Define finance-focused data quality dimensions (completeness, accuracy, consistency, timeliness)
• Create/maintain data quality rules, thresholds, and remediation workflows for governed datasets
• Partner with engineering and analytics teams to implement DQ controls in pipelines and interfaces
• Track and report DQ metrics, trends, and risk indicators to leadership and governance forums
4. Data Lineage, Metadata & Documentation
• Establish metadata standards for governed datasets, including business definitions and technical mappings
• Ensure lineage coverage between SAP S/4HANA objects, integration layers, and Data Hub entities
• Maintain documentation for data models, transformation logic, and dataset stewardship artifacts
• Ensure traceability of changes and support audits with evidence packs
5. Compliance, Security & Regulatory Support (Finance Context)
• Support governance requirements for regulatory and internal control obligations impacting finance data
• Collaborate with security/privacy/compliance partners to ensure governance aligns with policy controls
• Define retention, access considerations, and audit readiness requirements for governed datasets
• Ensure consistent handling of sensitive or regulated attributes used in finance reporting
6. Standards for Master Data, Reference Data & Finance Domains
• Define governance standards for master/reference data used by Finance (e.g., customers, vendors, cost centers, GL mappings)
• Drive standardization to reduce duplication and ensure consistent reporting and reconciliation
• Partner with business process owners to validate definitions and reconcile discrepancies
7. Stakeholder Management & Governance Enablement
• Run/participate in governance forums (data council, stewardship reviews, issue triage)
• Create governance playbooks, templates, and training materials for finance and technology stakeholders
• Provide SME guidance during onboarding of new datasets, data products, and use cases
• Build consensus across Finance, IT, Data Engineering, Analytics, and Platform teams
Required Qualifications:
Preferred Qualifications:
• Experience implementing data governance tooling or platforms (catalog/lineage/quality tooling)
• Knowledge of finance reporting processes, close activities, and reconciliation concepts
• Experience with data integration patterns and governance controls for ETL/ELT pipelines
• Certifications related to data governance, data quality, or data management (e.g., DAMA, CDMP, DG/MDG-related certifications)
Competencies:
• Governance Leadership: ability to set direction and drive adoption across cross-functional teams
• Data Quality Mindset: strong analytical approach with measurable outcomes
• Customer Partnership: business-oriented, responsive, and execution-focused
• Process & Control Orientation: strong ability to define repeatable governance processes
• Technical-Led Clarity: can bridge finance concepts and platform/engineering realities
Success Metrics (Examples)
• Improved data quality scores for governed finance datasets (baseline and target to be defined)
• Increased coverage of lineage/metadata for key finance entities in Data Hub
• Reduced governance cycle time for approvals and dataset onboarding
• Higher adoption of stewardship processes and governance decision outcomes
• Audit readiness achieved through complete documentation and evidence capture