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Mexico City, Mexico
Live, first seen by us 20 days agoWe 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.
Design, develop, and maintain scalable data pipelines using Databricks
Build data models in Bronze, Silver and Gold layers (Medallion Architecture)
Design and run benchmark questions to test accuracy of AI-generated answers
Translate business questions into semantic models that AI tools can query
Troubleshoot data pipelines, data quality issues, and performance problems
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.
Design, develop, and maintain scalable data pipelines using Databricks.
Build and maintain data models following Medallion Architecture principles (Bronze, Silver and Gold layers).
Design and execute benchmark questions and validation frameworks to evaluate the accuracy of AI-generated answers.
Translate business questions and analytical requirements into semantic models that AI tools can understand and query effectively.
Troubleshoot data pipelines, data quality issues, and performance problems.
Bachelor’s degree in Data Science, Computer Science, Engineering, Actuarial Science, Mathematics, Information Technology, or a related quantitative field.
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.
Experience with Databricks Genie.
Experience building semantic layers for analytics or AI applications.
Experience with Microsoft Fabric, Qliksense, Power BI, or similar analytics ecosystems.
Experience working in Agile environments and managing multiple analytics initiatives simultaneously.
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.
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Day 20
Similar jobs usually come down between day 6 and day 54.
From 10,824 similar postings that came down. Coming down is not always a hire.
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- 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.
- Advanced SQL skills. - Experience with Python for data processing and automation. - Experience developing ETL/ELT pipelines.
- 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 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.
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).
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.
- 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.
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.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
AI & Conversational Analytics
Analytics & Business Collaboration
Required qualifications
Preferred qualifications
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.
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Mexico City, Mexico
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.
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