Senior Analyst - Data & Analytics

ООО «ХАГЕМАЕР ГРУПП»; New York (NY); Hybrid; MXN 600,000 - 900,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Marsh is seeking a Senior Analyst in Data & Analytics to advance scalable data and AI-driven analytics solutions. You will join a data delivery team ensuring ETL quality and accuracy across sources and destinations.

This senior role combines data engineering with Generative AI and modern data platforms, requiring collaboration with stakeholders to translate requirements into reliable data products for analytics and AI use cases.

Qualifications

• Bachelor’s degree in a quantitative field and 4+ years in data analytics or data engineering.
• Strong SQL and Python for data processing and automation.
• Experience building ETL/ELT pipelines and data warehousing concepts.
• Experience with Databricks or comparable cloud data platforms.
• Excellent communication with business and technical stakeholders.

Responsibilities

• Design, build, and maintain scalable data pipelines with Databricks.
• Create data models following lakehouse concepts (Bronze-Silver-Gold).
• Transform, cleanse, and validate data using SQL and Python.
• Collaborate with stakeholders to translate requirements into technical solutions.
• Ensure data quality and pipeline performance; support analytics and AI use cases.

Skills

Advanced SQL

Python for data processing

ETL/ELT pipelines

Databricks

Data modeling

Communication with stakeholders

English proficiency

Education

Bachelor's degree in Data Science, Computer Science, Engineering, or related quantitative field

Tools

Databricks platform

SQL

Python

Power BI / BI tools

Job description

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.