Noblis - Bethesda, MD
posted 3 months ago
Noblis is seeking an experienced Data Architect/Engineer to join our team in the Bethesda, Maryland area. As a Data Architect/Engineer, you will play a critical role in shaping our client's enterprise architecture and driving cloud and data-related initiatives across the client's organization. Your responsibilities will span multiple areas, including strategic planning, cross-domain services, data security and compliance, data integrity, AI, and cloud platforms to enhance our customer's cloud and data ecosystem. In this role, you will contribute to the design and evolution of our client's enterprise cloud and data architecture, ensuring interoperability, security, and alignment with business goals. You will develop data and cloud strategies that consider long-term implications, anticipating future needs and trends. Collaboration is key, as you will work with teams across different domains (e.g., CIO, CDO, Security) to drive data integration initiatives and foster a data-driven culture. Your expertise will be essential in analyzing current data security practices, including data transiting between differing security level enclaves, to ensure compliance with relevant regulations. You will also analyze current data structures, tagging, and quality standards, and recommend solutions to analyze data across multiple cloud platforms (e.g., AWS, Azure, Google Cloud) for optimizing storage, compute, and analytics. Additionally, you will explore data generated by AI models and recommend ways to manage and integrate them into our client's data ecosystem. As a champion of the data mesh paradigm, you will promote decentralized data ownership and self-serve analytics. You will collaborate with the client's service providers for identity, credentialing, and access management to establish, enhance, and manage data access permissions. Your recommendations will also focus on optimizing compute resources and storage solutions for efficient data processing, as well as integrating qualitative insights by understanding the context and nuances of the data.