Cleared Chief Data Architect

• Noblis is seeking a cleared Data Architect supporting our customer in Bethesda, MD on a SETA contract.
• Enterprise Architecture & Strategy
• Define and implement a comprehensive  Big Data implementation framework aligned with the customer's mission objectives and IC enterprise standards.
• Develop and maintain the Enterprise Data Architecture ensuring integration with overall the customer and IC enterprise architectures.
• Translate mission needs into actionable Big Data system requirements, analytic tool specifications, and visualization tool requirements.
• Establish and enforce  Enterprise Data Standards and metrics to improve data normalization across the organization.
• Design architecture solutions supporting multiple data providers, structured/semi-structured/unstructured data types, and varying data velocity (static documents to real-time feeds).
• Data Mesh & Modern Architecture
• Design and implement  data mesh architecture across a dynamic workforce, enabling decentralized, domain-oriented data ownership.
• Architect scalable data solutions including data warehouses, data lakes, and data pipelines for enterprise-scale operations.
• Develop ML-ready data infrastructure supporting preprocessed, vectorized datasets for AI model training and deployment.
• Establish cloud-based data storage architectures leveraging emerging technologies and best practices.
• Governance & Compliance
• Ensure all data architecture solutions comply with  ICD 504 (Intelligence Community Data Management) requirements.
• Provide senior-level expertise on data policy and governance materials.
• Draft, coordinate, and implement processes for the customer data sharing, analysis, and interoperability.
• Integrate  ICD 503  (IT Systems Security Risk Management) and  ICD 505 (Artificial Intelligence) requirements into architectural designs.
• Ensure compliance with  NIST SP 800-53 Rev 4 security and privacy controls.
• Leadership & Collaboration
• Lead and mentor  multi-disciplinary teams including data engineers, data scientists, AI/ML engineers, and integration specialists.
• Organize and facilitate governance boards and working groups focused on data architecture and standards.
• Collaborate with stakeholders to examine and visualize data, extracting knowledge from large and complex digital data collections.
• Guide engineering solutions that balance technical innovation with policy compliance and security requirements.
• Improve data literacy across the customer workforce through training, documentation, and knowledge sharing.

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