Lead Coordinator - Metrics - Analytics and Reporting

Marsh McLennan is hiring a Lead Coordinator - Metrics - Analytics and Reporting in Mexico City, Mexico. Level rates it ; you can apply on Level.

AI in this role

databricks

rag

Company:

Marsh

Description:

Senior Analyst - Data & Analytics

About the role

We are looking for a Data & Analytics Senior Analyst to join our team and contribute to the development of scalable data and AI-driven analytics solutions.

This role is designed for a senior-level technical professional who combines strong data engineering capabilities with experience or interest in Generative AI, conversational analytics, and modern data platforms.

As part of a data delivery team, this role is responsible for ensuring ETL code quality by testing the data correctness, completeness and accuracy between sources and destinations.

Key responsibilities

Data Engineering & Architecture

Design, develop, and maintain scalable data pipelines using Databricks.
Build and maintain data models following Medallion Architecture principles (Bronze, Silver and Gold layers).
Perform data transformation, cleansing, standardization, and validation using tools like SQL and Python.
Design reusable and scalable datasets to support analytics, reporting, and AI use cases.
Troubleshoot data pipelines, data quality issues, and performance problems.

AI & Conversational Analytics

Participate in the design, development, and continuous improvement of Databricks Genie Spaces and AI-enabled analytics solutions.
Translate business questions and analytical requirements into semantic models that AI tools can understand and query effectively.
Design and execute benchmark questions and validation frameworks to evaluate the accuracy of AI-generated answers.
Explore new Generative AI capabilities that can improve how users interact with enterprise data.

Analytics & Business Collaboration

Work closely with business stakeholders, analysts, data engineers, and subject matter experts to translate business requirements into technical solutions.
Perform data analysis and validation to ensure consistency between source systems, analytical datasets, and business expectations.
Support the delivery of analytics projects from requirements gathering through production deployment and ongoing support.
Communicate technical concepts and project progress clearly to both technical and non-technical stakeholders.

Required qualifications

Bachelor’s degree in Data Science, Computer Science, Engineering, Actuarial Science, Mathematics, Information Technology, or a related quantitative field.
Approximately 4+ years of experience in Data Analytics, Data Engineering, Business Intelligence, or related roles.
Advanced SQL skills.
Experience with Python for data processing and automation.
Experience developing ETL/ELT pipelines.
Strong understanding of relational databases, data modeling, and data warehousing concepts.
Experience working with Databricks or comparable cloud data platforms.
Understanding of Medallion Architecture or modern lakehouse architectures.
Strong analytical and problem-solving skills.
Ability to communicate effectively with both business and technical stakeholders.
Professional working proficiency in English.

Preferred qualifications

Experience with Databricks Genie.
Experience building semantic layers for analytics or AI applications.
Exposure to Generative AI, LLMs, RAG, conversational BI, or natural-language-to-SQL solutions.
Experience with Microsoft Fabric, Qliksense, Power BI, or similar analytics ecosystems.
Experience working in Agile environments and managing multiple analytics initiatives simultaneously.

What we are looking for

We are looking for someone who is technically strong but also curious and business-oriented. The ideal candidate does not simply build pipelines based on predefined specifications; they understand why the data is needed, how it will be consumed, and how to design reliable data products that can support both traditional analytics and emerging AI use cases.

The successful candidate should be comfortable investigating complex problems, challenging assumptions, learning new technologies, and collaborating across technical and business teams

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

How we rate this

Lead Coordinator - Metrics - Analytics and Reporting at Marsh McLennan rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● 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. Open the description and count.

Key facts

Lead Coordinator - Metrics - Analytics and Reporting is an open job at Marsh McLennan.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Mexico City - Paseo.
The job was posted on October 16, 2026.
Seniority: lead.
Applications are handled by Marsh McLennan. Apply on Marsh McLennan

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGDatabricks

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through how you've used Databricks in your day-to-day work.
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: RAG and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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