Data Architect - FMS ACES

At Credence, we support our clients’ mission-critical needs, powered by technology. We provide cutting-edge solutions, including AI/ML, enterprise modernization, and advanced intelligence capabilities, to the largest defense and health federal organizations. Through partnership and trust, we increase mission success for war-fighters and secure our nation for a better future.

We are privately held, are repeatedly recognized as a top place to work, and have been on the Inc. 5000 Fastest Growing Private Companies list for the last 12 years. We practice servant leadership and believe that by focusing on the success of our clients, team members, and partners, we all achieve greater success.

Responsibilities:

• Translate business requirements into technology-driven data strategies, ensuring alignment with Army-wide data, cloud, and digital transformation initiatives. Define data standards and principles that support operational efficiency and decision-making.
• Design and implement a comprehensive data management framework that operationalizes the VAULTIS (Visible, Accessible, Understandable, Linked, Trustworthy, Interoperable, Secure) principles across the entire data lifecycle, including planning, specification, acquisition, maintenance, usage, archiving, retrieval, control, and purging. Contributes to the shift towards a data-centric approach by ensuring data is managed as a product, independent of specific systems or applications.
• Architect and govern a holistic data strategy that reduces redundancy, ensures data quality, and standardizes data models. The architecture will directly support a Zero Trust environment by securing data at the source. Enable high-quality data analytics to support mission-critical insights.
• Lead the execution of data quality improvements by profiling and remediating data issues, enabling a modern data mesh that treats data as a strategic asset and a product.
• Eliminate siloed data across disparate systems, enhance data autonomy, and establish robust data governance frameworks to ensure consistency, security, and accessibility.
• Ensure compliance with key architectural deliverables, including data dictionaries, entity relationship diagrams, data models, and documentation. Maintain and enforce adherence to the Army's Unified Data Reference Architecture (UDRA) and implement Data-as-a-Service (DaaS) patterns to facilitate seamless data exchange between domains.

Requirements:
• Translate business requirements into technology-driven data strategies, ensuring alignment with Army-wide data, cloud, and digital transformation initiatives. Define data standards and principles that support operational efficiency and decision-making.
• Design and implement a comprehensive data management framework that operationalizes the VAULTIS (Visible, Accessible, Understandable, Linked, Trustworthy, Interoperable, Secure) principles across the entire data lifecycle, including planning, specification, acquisition, maintenance, usage, archiving, retrieval, control, and purging. Contributes to the shift towards a data-centric approach by ensuring data is managed as a product, independent of specific systems or applications.
• Architect and govern a holistic data strategy that reduces redundancy, ensures data quality, and standardizes data models. The architecture will directly support a Zero Trust environment by securing data at the source. Enable high-quality data analytics to support mission-critical insights.
• Lead the execution of data quality improvements by profiling and remediating data issues, enabling a modern data mesh that treats data as a strategic asset and a product.
• Eliminate siloed data across disparate systems, enhance data autonomy, and establish robust data governance frameworks to ensure consistency, security, and accessibility.
• Ensure compliance with key architectural deliverables, including data dictionaries, entity relationship diagrams, data models, and documentation. Maintain and enforce adherence to the Army's Unified Data Reference Architecture (UDRA) and implement Data-as-a-Service (DaaS) patterns to facilitate seamless data exchange between domains.