Data Operations Manager (compensation data analysis)

Aon is hiring a Data Operations Manager (compensation data analysis) in Mexico City, Mexico. Level rates it ; you can apply on Aon.

Level's read on this job

Little AI ●○○○ is how Level rates this role: aI is not part of the work.
Level classifies it as a mid-level role.
Level lists 1,000+ other open roles at Aon.

AI in this role

Data Operations Manager– Compensation Data Analysis Please apply using your English CV. About the Role As a Data Operations Manager at Aon Services Corporation, you will play a key role in delivering high‑quality compensation and survey data solutions to clients in the US. You will be responsible for managing survey input, validating data, conducting initial job matching, and supporting analyses that help organizations make better decisions on pay and rewards. Working closely with colleagues in the US and Mexico, you will ensure a seamless client experience through accurate data, timely responses, and strong collaboration. This role requires fluent English, strong analytical capabilities, and a high level of attention to detail. What the Day Will Look Like In this role, you will: Complete survey input on behalf of clients, ensuring accuracy and consistency. Conduct initial job matching, applying your analytical skills and attention to detail. Verify the accuracy and validity of submitted data, adhering to Aon’s quality standards. Collaborate closely with internal teams, including Data Solutions and Client Success Managers in the US and Mexico, to resolve compensation and survey input issues. Respond to client inquiries regarding compensation and survey data, providing clear, thoughtful analysis. Develop and maintain positive collaborator and client relationships through regular, proactive communication. Recognize and translate client questions, comments, and requests into potential opportunities for supplemental report sales or consulting assignments. Analyze compensation and survey reports and support the review, development, and modification of reports for client use. Assist with various ad‑hoc projects, demonstrating flexibility and a continuous‑improvement mindset. How This Opportunity Is Different This role places you at the intersection of data, client service, and human capital decision‑making. You will: Work directly with compensation and survey data that informs critical client decisions on pay, talent, and rewards. Partner with diverse teams across the US and Mexico, gaining exposure to different industries, roles, and market practices. Have the opportunity to identify and influence new opportunities for Aon, such as additional reports or consulting work. Grow your analytical, client‑facing, and project coordination skills in a global firm committed to professional development and innovation, including the use of AI‑enabled tools. Skills and Experience That Will Lead to Success Required: Fluent English, with strong written and verbal communication skills to work effectively with US‑based clients and internal stakeholders. Strong data management skills, process orientation, and outstanding attention to detail. Proven analytical skills, both qualitative and quantitative. Ability to manage multiple tasks and priorities while meeting strict deadlines. Strong collaboration skills and the ability to operate in a cooperative, team‑focused environment. Strong skills in Microsoft Excel and comfort working with AI‑enabled technology. Preferred: Approximately 3 to 5 years of experience in compensation, total rewards, or related human resources fields. Approximately 3 to 5 years of experience managing projects or workstreams. #LI-KA2 #Hybrid 2587915

How we rate this

Data Operations Manager (compensation data analysis) at Aon rates 37 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.