Total Rewards Partner
The Role
We are looking for a Total Rewards Partner to support EFG’s global strategy across 40+ countries by serving as the core technical expert and data strategist for the Total Rewards function. Reporting to Global Total Rewards, this role balances data-driven advisory with hands-on execution. You will partner directly with People teams, Finance, and business leaders to guide reward decisions, while bringing the technical rigor required to build robust compensation models, ensure data integrity, and leverage modern HR tech and AI to drive automation and scalability across EFG.
What you will do
Financial Modeling & Global Cycles: Own and build complex financial models in Excel/Google Sheets for salary structures, annual review cycles, short- and long-term incentives (STI/LTI), and budget forecasting;
Analytics, AI & Modern HR Tech: Manage global compensation datasets, dashboards, and reporting. Implement practical AI, process automation, and HRIS integrations (e.g., HiBob) to scale analytical capabilities and eliminate manual work;
Benchmarking, Job Architecture & Pay Equity: Execute quantitative market analyses using survey providers (Mercer, Radford, etc.), maintain global job architecture and leveling, and run pay equity reviews;
Business Advisory & Data Storytelling: Partner with People teams, Finance, and business leaders to translate complex quantitative analysis into clear, actionable advice that supports strategic pay decisions.
What we are looking for
5+ years of Total Rewards or Compensation experience in an international, multi-region environment;
Advanced financial modeling & analytical skills in Excel/Google Sheets, with hands-on HRIS experience;
Deep technical expertise in market benchmarking (Mercer, Radford, etc.), job architecture, pay equity, and annual review cycles;
Demonstrated interest or practical experience applying AI, automation, and HR technology to streamline workflows and decision support;
Strong business partnering skills with the ability to translate complex data into clear business recommendations and influence stakeholders;
High attention to detail, strong data governance mindset, and fluent written and spoken English.