Job Title

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 modeling 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.