Data Modeler Hybrid Data Environments

Job Summary :

We are in search of an experienced Data Modeler who possesses a deep understanding of traditional data stores such as SQL Server and Oracle DB, as well as proficiency in Azure/Databricks cloud environments. The ideal candidate will be adept at comprehending business processes and deriving methods to define analytical data models that support enterprise-level analytics, insights generation, and operational reporting.

Key Responsibilities :

- Collaborate with business analysts and stakeholders to understand business processes and requirements, translating them into data modeling solutions.

- Design and develop logical and physical data models that effectively capture the granularity of data necessary for analytical and reporting purposes.

- Migrate and optimize existing data models from traditional on-premises data stores to Azure/Databricks cloud environments, ensuring scalability and performance.

- Establish data modeling standards and best practices to maintain the integrity and consistency of the data architecture.

- Work closely with data engineers and BI developers to ensure that the data models support the needs of analytical and operational reporting.

- Conduct data profiling and analysis to understand data sources, relationships, and quality, informing the data modeling process.

- Continuously evaluate and refine data models to accommodate evolving business needs and to leverage new data modeling techniques and cloud capabilities.

- Document data models, including entity-relationship diagrams, data dictionaries, and metadata, to provide clear guidance for development and maintenance.

- Provide expertise in data modeling and data architecture to support the development of data governance policies and procedures.

Qualifications :

- Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field.

- Minimum of 5 years of experience in data modeling, with a strong background in both traditional RDBMS and modern cloud-based data platforms.

- Proficiency in SQL and experience with data modelling tools (e.g., ER/Studio, ERwin, PowerDesigner).

- Familiarity with Azure cloud services, Databricks, and other big data technologies.

- Understanding of data warehousing concepts, including dimensional modeling, star schemas, and snowflake schemas.

- Ability to translate complex business requirements into effective data models that support analytical and reporting functions.

- Strong analytical skills and attention to detail.

- Excellent communication and collaboration abilities, with the capacity to engage with both technical and non-technical stakeholders.