Compensation Advisor

Role Overview

Compensation Adviser – Global Compensation, Market Pricing & Analytics

The Compensation Adviser will support the Global Compensation, Recognition and Tools COE through compensation analytics, market intelligence, market pricing, survey administration, and project support across NTT DATA's global organization.

The role will work closely with Global Reward COE colleagues, Regional and Country Total Reward Partners, and external compensation survey providers to support compensation initiatives across Consulting, Specialty Businesses, Business Services, and corporate functions.

A key focus of the position will be translating complex compensation and market data into clear, actionable insights. The successful candidate will be expected to go beyond data reporting by identifying anomalies, testing assumptions, assessing market relevance, and highlighting issues requiring further review.

The role requires strong analytical capability, advanced Excel and data-management skills, attention to detail, and a solid understanding of compensation fundamentals. The individual should be comfortable working with broad direction, managing multiple priorities, and progressively taking ownership of defined analytical and operational activities.

Key Responsibilities

Market Pricing & Benchmarking

• Conduct market pricing and benchmarking for jobs across multiple countries, job families, and business areas using approved compensation survey sources.
• Analyze job content, responsibilities, organizational scope, talent group, and career level to support appropriate survey job matching.
• Compare market data across multiple survey providers and identify material differences, anomalies, or questionable observations.
• Support the development and validation of market reference points, salary range midpoints, and supporting range analytics.
• Perform level-to-level progression, range-width, internal-pay, and market-positioning analyses.
• Document market-pricing recommendations, assumptions, data sources, and rationale to maintain a clear audit trail.

Compensation Surveys & Market Intelligence

• Coordinate annual and ad hoc compensation survey activities, including data preparation, submission, validation, and quality checks.
• Work with compensation survey providers such as Mercer, Aon Radford, WTW, and other relevant market-data vendors.
• Analyze survey participant populations, peer groups, industry cuts, and other market segments to assess relevance for NTT DATA.
• Maintain survey inventories, participation information, effective dates, aging assumptions, and supporting documentation.
• Monitor relevant compensation-market developments and identify insights that may influence benchmarking or market-pricing decisions.

Compensation Analytics & Quality Assurance

• Analyze large compensation and employee datasets to identify trends, anomalies, inconsistencies, and data-quality issues.
• Develop structured analyses supporting compensation decisions, market competitiveness, and internal consistency.
• Build and maintain Excel-based analytical tools, dashboards, review files, and management reports.
• Perform quality assurance across compensation outputs, including job matches, market values, salary ranges, and progression relationships.
• Investigate unusual results and determine whether issues arise from data quality, survey matching, methodology, or genuine market conditions.

Project & Stakeholder Support

• Support global compensation projects through data analysis, documentation, project tracking, and preparation of stakeholder materials.
• Prepare structured review packs for Total Reward Partners and consolidate market-pricing feedback and exceptions.
• Conduct first-level analysis of compensation questions raised by Total Reward Partners and escalate complex methodology or policy matters to the appropriate COE lead.
• Collaborate with global and regional colleagues to resolve data issues and ensure consistency of analysis.
• Coordinate with external vendors on survey participation, data requests, and analytical requirements.

Technology & Process Improvement

• Identify opportunities to automate repetitive compensation processes and improve data quality, reporting, and analytical efficiency.
• Use advanced Excel, analytics tools, and approved AI technologies to support analysis, quality assurance, documentation, and reporting.
• Support the development and testing of compensation tools and standardized analytical processes.
• Maintain clear process documentation and version-controlled working files.

Required Experience & Qualifications

• Bachelor's degree in Human Resources, Business, Finance, Economics, Statistics, Data Analytics, or a related field.
• 8-10 years of relevant experience in Compensation, Total Rewards, HR Analytics, Workforce Analytics, or a comparable analytical role.
• Demonstrated experience working with compensation data, salary benchmarking, or market-pricing analysis.
• Strong Microsoft Excel capability, including:
• Pivot Tables
• XLOOKUP and INDEX-MATCH
• Advanced formulas
• Data validation and reconciliation
• Large dataset manipulation
• Power Query
• Reporting and dashboard development
• Strong analytical and problem-solving skills, with the ability to identify data anomalies and investigate root causes.
• Ability to interpret data and develop meaningful conclusions rather than simply producing reports.
• High attention to detail and commitment to data accuracy.
• Ability to manage multiple priorities and deliver high-quality work with broad direction.
• Strong written and verbal communication skills.
• Experience working across countries, regions, or business units.

Preferred Qualifications

• Experience within Technology, IT Services, Consulting, or Professional Services.
• Exposure to global compensation programs and multi-country market pricing.
• Experience with compensation survey platforms such as Mercer, Aon Radford, WTW, Comptryx, Remchannel, or equivalent providers.
• Experience with Power BI or comparable data-visualization tools.
• Exposure to AI-enabled analytical tools, automation, or workflow improvement.
• Familiarity with job architecture, career frameworks, and salary-range design.

Key Success Factors

The successful candidate will:

• Demonstrate curiosity and challenge questionable data rather than accepting outputs at face value.
• Understand that job content and scope, not job title alone, drive market matching.
• Distinguish between a market data point and a compensation recommendation.
• Identify inconsistencies across survey sources, jobs, levels, and countries.
• Produce analysis that is accurate, traceable, and easy for another compensation professional to understand.
• Make sensible recommendations within defined methodology and escalate appropriately where policy or senior judgement is required.