Data Architect

Overview

DecisionPoint seeks a Data Architect to lead the design, governance, and validation of enterprise data architectures for a Department of Defense (DoD) modernization program supporting Casualty and Mortuary Affairs (CMA) operations across all Service components. The Data Architect will define and maintain logical and physical data models across Impact Level (IL) 2, 4, and 5 environments, ensuring high availability, data integrity, and secure data exchange within a cloud-hosted ecosystem.

The Data Architect will work closely with system engineers, database administrators, and developers to standardize schemas, improve data quality, and align data governance with DoD enterprise architecture standards.

This position is fully remote.

Note: By applying to this position, you acknowledge and consent to having your resume included in an active competitive government contract bid.

The Data Architect will:

• Develop and refine conceptual, logical, and physical data models that support cloud-hosted information systems operating in IL2, IL4, and IL5 environments.
• Design and document data schemas, entity relationships, and data flow diagrams in accordance with DoD and Defense Information Systems Agency (DISA) standards.
• Collaborate with technical teams to ensure data models align with mission workflows, integration requirements, and information assurance policies.
• Implement and maintain data integrity rules, referential constraints, and validation processes across test, pre-production, and production environments.
• Develop data architecture documentation and metadata repositories, including data dictionaries, mapping specifications, and lineage tracking.
• Support data migration and transformation from legacy systems, ensuring source-to-target mapping accuracy and reconciliation.
• Participate in architecture design reviews, identifying performance optimization and scalability opportunities.
• Align database structures with security and compliance mandates such as DoD Cybersecurity Policy Chart, DoDAF, and DISA Cloud Computing Security Requirements Guide (CC SRG).
• Conduct post-deployment validation and testing to confirm data accuracy and structural consistency across environments.
• Lead efforts to implement and manage data lakes, warehouses, and API-based data services that support analytics, reporting, and inter-Service data sharing.
• Collaborate with cybersecurity and network teams to ensure data architectures support Zero Trust and data encryption policies.
• Provide technical mentorship to database administrators and developers on best practices for performance tuning, data normalization, and cloud database management.

Clearance Requirement:

• Must hold an active Top Secret clearance.

Education:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field.

Experience:

• Minimum 7 years of experience in data architecture, database design, or data engineering within large-scale federal or defense environments.
• Experience supporting cloud-hosted systems and data models across multi‑level (IL2‑IL5) environments in AWS Gov Cloud or equivalent.

Technical Knowledge:

• Expertise in logical and physical data modeling, schema optimization, and metadata management.
• Hands‑on experience with AWS RDS, Aurora, or Postgre
  
  SQL, and familiarity with data warehousing and ETL design.
• Understanding of data governance frameworks, data quality assurance, and data lifecycle management.
• Knowledge of DoD and DISA standards, including DoDAF, CC SRG, and STIGs for database security and compliance.
• Familiarity with API‑driven data exchange, data lake architectures, and BI/reporting systems.

Certifications (Preferred):

• AWS Certified Data Analytics – Specialty or AWS Solutions Architect.
• TOGAF or DoDAF certification.
• DoD 8570/8140 certification (Security⁺ CE, CISSP, or equivalent).

Skills:

• Strong analytical and conceptual thinking skills.
• Exceptional attention to detail in data validation and model integrity.
• Ability to document complex architectures clearly and concisely.
• Effective collaboration across multidisciplinary technical teams.
• Commitment to innovation, data quality, and mission…