Data Architect / Data Analyst with Security Clearance

About the role

ThinkTek LLC is a fast-growing Certified SBA 8(a) and Service-Disabled Veteran-Owned Small Business (SDVOSB). We specialize in providing management and technology consulting services to support the business and technology modernization efforts of the Federal Government. ThinkTek was formed with the specific purpose of providing its clients a tailored solution around Program & Project Management, Strategic Planning, and IT Services.

ThinkTek is seeking an experienced Data Architect / Data Analyst to support enterprise business process re-engineering and the development of a comprehensive, end-to-end information and data architecture. The successful candidate will be responsible for identifying and documenting the information assets required to execute and govern re-engineered business processes and translating high-level information requirements into detailed, granular data elements. This role will support the development of an enterprise canonical data model by systematically decomposing information assets, documenting data relationships and dependencies, and mapping the complete data lifecycle throughout business processes. The position will maintain a comprehensive Data Dictionary and Requirements Traceability Matrix (RTM) to ensure clear, bi-directional alignment between mission capabilities, future-state processes, business rules, information assets, data elements, and performance measures. The ideal candidate will possess a strong understanding of business architecture, data architecture, process modeling, requirements management, data governance, and enterprise information management, with the ability to translate complex business processes into structured data and information requirements.

Responsibilities

• Identify, define, analyze, and document the information assets required to execute, manage, measure, and govern re-engineered business processes.
• Analyze target-state business processes to determine the information required at each stage of the process lifecycle.
• Systematically decompose high-level information assets into granular data elements to support development of an end-to-end canonical data model.
• Define data-element attributes, relationships, ownership, usage, dependencies, and business context.
• Identify relationships and dependencies between information assets,