Master Data & Reference Lead: Modernization & Governance

Everest Group, Ltd.; New Jersey; On-site; USD 156,000 - 180,000; Full time

Job summary

Everest Global Services, Inc. seeks a Master and Reference Data Management Lead in Warren, NJ to shape master/reference data capabilities across our global Insurance business. You will establish governance, data quality, and trusted records, and lead modernization efforts across the data platform.

This hands-on leadership role requires coordinating with Technology and Architecture to define ownership, controls, and adoption, driving value from data products enterprise-wide.

Qualifications

• 8–10 years in data management, governance or related disciplines.
• Experience designing or implementing MD/RD capabilities and governance.
• Experience with cloud-based data platforms and modern architectures.
• Ability to translate business needs into data requirements and controls.

Responsibilities

• Define and drive the Master Data Management and Reference Data Management strategy, target state and roadmaps.
• Lead requirements for platform modernization and partner with Technology/Architecture.
• Establish ownership boundaries, governance, and approval workflows across teams.
• Oversee day-to-day data operations, issues, changes, risks and dependencies.
• Define measures for data quality, adoption, and change activity to drive improvement.

Skills

Master data management

Data governance

Stakeholder management

Cloud platforms

Data quality

Architecture collaboration

Education

Bachelor's degree in a relevant field

Tools

ETL tooling

Metadata management tools

SQL/Database knowledge

Job description

Everest Global Services, Inc. seeks a Master and Reference Data Management Lead in Warren, NJ to shape master/reference data capabilities across our global Insurance business. You will establish governance, data quality, and trusted records, and lead modernization efforts across the data platform.

This hands-on leadership role requires coordinating with Technology and Architecture to define ownership, controls, and adoption, driving value from data products enterprise-wide.