Data Architect designs, creates, and manages an organization’s data architecture. Maps the flow of data to align with business processes, and ensures data accuracy, availability, and security.
Duties & Responsibilities
- Modern Data Analytics.
- Provide professional management, systems engineering and technical assistance support to: represent the different building blocks that make up the enterprise and its interrelationships as well as the principles guiding their design and evolution over time, to enable a standard, responsive and efficient delivery of operational and strategic objectives; develop and maintain business, systems, and information processes to support enterprise management in support of mission needs; develop information technology rules and requirements that describe baseline and target architectures; establish a common architecture consisting of business process, information, data, application and technology architecture layers; create key models and practices that describe the baseline and target architectures, in line with the enterprise and I&T strategy; define requirements for taxonomy, standards, guidelines, procedures, templates and tools, and provide a linkage for these components; improve alignment, increase agility, improve quality of information and generate potential cost savings through initiatives such as re-use of building block components; represent the different building blocks that make up the enterprise and its interrelationships as well as the principles guiding their design and evolution over time, to enable a standard, responsive and efficient delivery of operational and strategic objectives. Assistance can include, but is not exclusive to Provide technical assistance to: ensure data is postured for secure discovery, access, and integration between mission partners realizing data as a strategic asset; ensure effective utilization of the critical data assets to achieve enterprise goals and objectives; achieve and sustain effective management of the enterprise data assets across the data life cycle, from creation through delivery, maintenance and archiving; translate business/mission requirements into data management and technology requirements: define data standards, strategy, principles and architectures; visualize and design the AF IC Information Environment enterprise data management framework and operational data architectures, which describe the processes and information used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. In accordance with IC and DoD direction, guidance and services of common concern, as well as industry frameworks, provide standard common business/mission vocabulary, ontology; express strategic requirements; outline high-level integrated designs to meet those requirements and align with enterprise data strategy and related mission and operational data architectures. Assistance can include, but is not exclusive to:
- Data Literacy Planning. Analyze the current state of data literacy and effectiveness of the AF IC Information Environment workforce in effective use, interpretation of data and scaling data analytics practice; identify organizational needs at programs/mission levels and initiatives to improve overall data literacy.
- Enterprise Data Mapping. Develop high-level depictions of the end-to-end data life cycle at the enterprise level, enabling a visualization of both internal and external data interactions. Enterprise data mapping provides transparency for data life cycle within the AF IC Information Environment and can be utilized in data triage, modernization, and data analytics initiatives.
- Data Governance. Perform initial assessment to understand current data processes and organizational context and establish Data Governance as an authoritative function under the CDO. Support the activities to plan, control and monitor data management through a well-defined organizational structure and set of processes.
- Data and Analytics Capability Portfolio Management Support. Support activities to assess capabilities and determine the appropriate mix of investments and strategic projects to provide foundational and transformational analytics capabilities that promote data-driven decision making.
- Data Asset Inventory and Cataloging. Develop a live inventory of key data assets through various sources, capture it in an agreed format and populate available data catalog with relevant metadata.
- Data Sharing Platform Design. Assess the current state of AF IC Information Environment data infrastructure, identifying gaps and pain-points, designing target state architectures (conceptual and logical) for data integration, data sharing, and full-life cycle data management that supports ISR vision and is based on IC guidance, informed by DoD guidance and industry best practices.
- Ontology. Assist with educating and exposing/registering AF IC Information Environment content with Defense Intelligence Core Ontology (DICO). Provide recommendations of various domain knowledge models to integrate data objects across the IC, DoD and AF. Support development of near-/mid-/far-term objectives and recommend candidate efforts to advance AF Object Base Intelligence (OBI) with mission partners. Assist in development, publication and education of ISR domain ontologies for use across missions and across AF ISR mission partners; interface with ontology efforts including DIA, DoD and AF CDAOs, NATO, Joint Services and other AF efforts; provide expertise, guidance, and knowledge for best practices on ontology implementation; maintain artifacts such as ontologies, taxonomies, dictionaries, and queries; maintain master copy of semantic dictionary, control versioning to ensure updates are pushed appropriately; maintain ontology resources and training material for the AF ISR community. Implement ontologies using IC and government approved platforms/environments that use modern, widely-adopted industry standards.
- Provide expertise on Object Management System (OMS) implementation. Facilitate meetings with enterprise stakeholders and support the development a cohesive enterprise strategy and approach.
- Automation, Augmentation and Artificial Intelligence (AI) (AAA) for Sense-Making.
- Provide technical assistance for identifying opportunities, in cooperation with agency-wide efforts, to address unique mission challenges with AI solutions that incorporating machine learning (ML), neural networks, intelligent process design and Robotic Process Automation (RPA).
- Provide strategic tools and digital infrastructure services support to rapidly discover use cases, identify applicable artificial intelligence methods, and deploy scalable solutions across the AF IC Information Environment. Assistance can include, but is not exclusive to:
- Use Case Discovery and Selection in coordination with MAJCOM and DAF stakeholders.
- Process Automation and Workflow Mapping.
- AI Performance and Confidence Standards framework
- MLOps Framework
|Job Category||Architect, Database|
|Experience||0 - 3 Years’ Experience required|