
Data Modeller
4 weeks ago
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.
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