Job Description

Job Summary: The Senior Data Modeler will be responsible for designing and implementing data models optimized for storage, retrieval, and analytics within a Databricks environment. This role involves working with various stakeholders to define and implement best practices for data modeling and data integration, ensuring data quality, consistency, and security. Location: Washington, District of Columbia, United States, Responsibilities: - Design and implement data models optimized for storage, retrieval, and analytics within Databricks. - Develop ELT pipelines to extract data from various sources, transform it, and load it into the central data lake. - Integrate data from heterogeneous sources into Databricks, ensuring data quality, consistency, and lineage. - Optimize data processing workflows and SQL queries in Databricks for performance, scalability, and cost-effectiveness. - Implement security measures to ensure data integrity, confidentiality, and compliance within the centralized data lake environment. - Define best practices for the implementation of the Bronze/Silver/Gold data layers of the lakehouse. - Provide data model documentation and artifacts generated from data, data dictionary, data definitions, etc. - Collaborate with product owners, system architects, data engineers, and vendors to create data models. Required Skills & Certifications: - At least ten or more years of experience in AI, Data Science, or Software Engineering, including knowledge of the Data ecosystem. - Bachelor's degree in Computer Science, Information Systems, or a related field. - Expertise in designing and implementing data models optimized for storage, retrieval, and analytics. - In-depth knowledge and hands-on experience with the Databricks platform. - Proficiency in developing ELT pipelines using Databricks tools and Spark. - Experience integrating data from heterogeneous sources into Databricks. - Ability to optimize data processing workflows and SQL queries in Databricks. - Understanding of data governance principles and implementing security measures. - Proficiency in writing complex SQL queries and Spark code (Scala/Python). - Understanding of cloud computing principles and architecture. - Leverage financial industry expertise to define conceptual, logical and physical data models in Databricks to support new and existing business domains Preferred Skills & Certifications: - Basic knowledge of data visualization tools (e.g., Tableau). - Familiarity with government cloud deployment regulations/compliance policies such as FedRAMP, FISMA, etc. Special Considerations: - Not specified. Scheduling: - Not specified.

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