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.
