HQE Integrated Architecture Advisor

Full Job Description

The primary purpose of this position is being responsible for the designing and implementing a cohesive architecture that integrates data governance and data quality frameworks with data analytics tools and business system to support the development of a robust didgital analytic ecosystem.

Eligibility will be based upon a clear showing the applicant has training, education and experience of the scope and quality sufficient to effectively carry-out the duties of the position.

Candidates must exemplify the corporate perspective, leadership vision, broad experience and character needed in for this position..

HQEs contribute in a variety of occupational fields, such as soft and hard sciences, engineering, technology, human resources, business, transformation, education, medicine, languages, and logistics.

HQEs may be hired to mentor, lead, oversee, direct, manage, and or consult on DoD programs and initiatives, including high profile and fast track assignments.

HQEs serve at the pleasure of the Appointing Official and may be terminated at any time. When practicable, they should be given no less than 3-days' advance notice.

Additional requirements include: executive-level experience in IT/ET architecture concepts and program management to include emerging technologies not currently in use within the DoD; a high level of personal initiative, creative problem solving skills, and innovative thought; and the ability to present and defend independent positions at the highest levels of government Major Duties:

MAJOR DUTIES AND RESPONSIBILITIES: Develop and maintain an integrated architecture blueprint that aligns with the organization's strategic goals and technology roadmap.

Design systems that integrate data governance, data quality, analytics tools, and business systems into a seamless framework.

Implement data governance policies and procedures to ensure data integrity, privacy, and compliance with federal regulations.

Develop and enforce data quality standards to ensure that the data used for analysis is accurate, complete, and reliable.

Integrate advanced data analytics tools and business intelligence software into the architecture to facilitate data-driven decision-making.

Act as a liaison between IT, data management teams, and business units to ensure that the architecture meets all functional requirements.

Advise cross-functional teams in the planning and implementation of architectural projects. Manage timelines, resources, and risks associated with architecture projects.

Mentor and provide guidance to junior architects and other team members. Ensure the architecture supports both current and future business needs in an agile and scalable manner.

Work closely with business analysts and data scientists to ensure that the analytics tools are effectively used to generate insights.

Communicate architectural decisions, plans, goals, and strategies to stakeholders at all levels of the organization.

Collaborate with external vendors and service providers to integrate third-party solutions into the ecosystem.

Monitor emerging technology trends and evolving business needs to recommend architectural improvements. Conduct regular reviews of the existing architecture to identify and implement enhancements.

Promote innovation in the use of data and technology through continuous improvement initiatives. 10 years of experience in managing complex data architecture projects in a large organization.

Proficiency in creating and maintaining conceptual, logical, and physical data models is crucial. This includes understanding various data modeling standards and methodologies.

Familiarity with SQL and NoSQL databases, data warehousing solutions, and big data technologies like Hadoop and Spark is essential for managing and integrating diverse data sources.

Expertise in ETL (Extract, Transform, Load) processes, data pipelines, data lakes, and data warehouses is necessary for combining data from different sources into a unified view.

Skills in programming languages such as SQL, Python, Java, and others are important for developing custom data solutions and automating data processes.

Understanding of data governance frameworks and compliance standards (e.g., GDPR, HIPAA) to ensure data integrity, privacy, and regulatory compliance.

Knowledge of cloud platforms (AWS, Azure, Google Cloud) and cloud integration models (SaaS, PaaS, IaaS) is vital for leveraging cloud technologies in data architectures.

An advanced degree in computer science, information systems, or data science. Ability to use data analysis tools and techniques to extract insights and trends from data.

Proficiency in data visualization tools is also important for presenting data findings.

Excellent communication skills to effectively convey complex data concepts to non-technical stakeholders and collaborate with various departments and IT teams.

Ability to guide projects and teams towards achieving data-related objectives.

T Skills in managing multiple projects simultaneously, ensuring timely delivery, and identifying and mitigating risks related to data management and security.

Ability to work closely with business analysts, data scientists, IT teams, and external vendors to ensure that the architecture meets all functional requirements.