NavitsPartners
Job Title:
Senior Data Modeler Location:
Washington, DC (Onsite/Hybrid options may apply) Type:
Contract Job Description:
We are seeking a highly skilled Senior Data Modeler with a strong background in the financial industry and deep expertise in Databricks on AWS. The ideal candidate will play a key role in defining and optimizing data models that support both new and existing business domains. This role demands a strategic thinker who can collaborate across teams and deliver robust, scalable, and high-performance data solutions. Key Responsibilities: Design and implement conceptual, logical, and physical data models in Databricks to support enterprise-level business domains Collaborate with product owners, system architects, data engineers, and vendors to develop data models that are optimized for performance, compute, and storage Define and enforce best practices for Bronze/Silver/Gold lakehouse architecture layers Generate comprehensive documentation including data models, dictionaries, definitions, and metadata artifacts Drive governance standards for data integrity, security, and compliance Required Skills and Qualifications: 10+ years of experience in AI, Data Science, or Software Engineering, with deep expertise in enterprise data ecosystems Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent professional experience) Proven experience in data modeling-designing optimized storage, retrieval, and analytics models in Databricks on AWS Hands-on expertise in Databricks SQL, Runtime, clusters, notebooks, and integrations Proficiency in building ELT pipelines using Databricks tools and Apache Spark Strong background in data integration from various sources such as relational databases, APIs, and flat files Skilled in performance optimization-partitioning, caching, clustering, and Spark tuning techniques Solid understanding of data governance, including security and compliance frameworks Proficient in advanced SQL and Spark (Scala or Python) for data transformation and analysis Familiarity with cloud architecture, particularly AWS services Basic experience with data visualization tools (e.g., Tableau) for reporting and analytics Knowledge of government cloud compliance standards such as FedRAMP and FISMA is a strong plus
Senior Data Modeler Location:
Washington, DC (Onsite/Hybrid options may apply) Type:
Contract Job Description:
We are seeking a highly skilled Senior Data Modeler with a strong background in the financial industry and deep expertise in Databricks on AWS. The ideal candidate will play a key role in defining and optimizing data models that support both new and existing business domains. This role demands a strategic thinker who can collaborate across teams and deliver robust, scalable, and high-performance data solutions. Key Responsibilities: Design and implement conceptual, logical, and physical data models in Databricks to support enterprise-level business domains Collaborate with product owners, system architects, data engineers, and vendors to develop data models that are optimized for performance, compute, and storage Define and enforce best practices for Bronze/Silver/Gold lakehouse architecture layers Generate comprehensive documentation including data models, dictionaries, definitions, and metadata artifacts Drive governance standards for data integrity, security, and compliance Required Skills and Qualifications: 10+ years of experience in AI, Data Science, or Software Engineering, with deep expertise in enterprise data ecosystems Bachelor's degree in Computer Science, Information Systems, or a related field (or equivalent professional experience) Proven experience in data modeling-designing optimized storage, retrieval, and analytics models in Databricks on AWS Hands-on expertise in Databricks SQL, Runtime, clusters, notebooks, and integrations Proficiency in building ELT pipelines using Databricks tools and Apache Spark Strong background in data integration from various sources such as relational databases, APIs, and flat files Skilled in performance optimization-partitioning, caching, clustering, and Spark tuning techniques Solid understanding of data governance, including security and compliance frameworks Proficient in advanced SQL and Spark (Scala or Python) for data transformation and analysis Familiarity with cloud architecture, particularly AWS services Basic experience with data visualization tools (e.g., Tableau) for reporting and analytics Knowledge of government cloud compliance standards such as FedRAMP and FISMA is a strong plus