About Company:

Our Client is French multinational company.It provides investment management ,financial servicesand insurance and reinsurance products for corporate, small-to-medium enterprises, and individual consumers.

An Ideal Candidate:

• The ideal candidate must possess 5-10 years of experience in Data Modelling. Good communication skills to coordinate between business stakeholders & engineers.Ability to establish relationships with stakeholders quickly in order to collaborate on use cases. Bachelor’s/Master's Degree in Computer Science or related field.Proficient in Data Modelling.Experience in Data modeling tools ( Tool - Erwin). building ER diagram, ERWIN, and Visio data modelling/UML tool. Experience in Entity relationship, dimensional, and NOSQL modelling as appropriate to data warehousing, Star scheme, business intelligence, and analytical approaches using IE or other common notations. Experience in SQL, DDL, DML, and Pyspark scripting. Experienced in writing scripts for data transformation using SQL, DDL, DML, and Pyspark.Exposure in Azure cloud, Azure Data Databricks.Proven knowledge of physical and logical data modelling in a data warehouse environment including the successful creation of conformed dimensional models from a range of legacy source systems alongside modern SaaS/Cloud business applications.

Key Competencies:

• The Data Modeler designs fit-for-purpose conceptual, logical, and physical data models in-line with business requirements to serve analytical, business intelligence, and operational use cases primarily within the data platform.
• Elicit, analyze, and document data requirements in support of analytical, business intelligence, warehousing and other business use cases for the data platform using a range of techniques including source data analysis, documentation, interviews, and data modelling workshops
• Create and maintain data models appropriate to the need and that conform to data modelling standards.
• Produce and maintain metadata (including relationships, calculation logic etc.) and documentation to accompany data models using data modelling tools where appropriate.
• Ensure models will provide data structures that meet the required range of non-functional requirements including performance, extensibility, change capture (SCD etc), understandability, and maintainability.
• Create and maintain specifications for data transformation in both documentation (Source To Target Mapping) and scripting.
• Agree artefacts, models, documentation, and scripts with relevant business owners, stewards, SMEs, and technical stakeholders.
• Test models and transformation scripts to ensure they meet requirements.
• Perform day-to-day data model and script maintenance to tune performance, respond to changes, and in support of IT issues.
• Advise data engineers, visualization developers, and other consumers of models and data specifications in the interpretation of data models and structures and the understanding of data requirements.
• Contribute to the definition of data dictionaries, and business glossaries.