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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