> Markdown version of [/jobs/ext/1993819-data-architect](https://www.wearedevelopers.com/jobs/ext/1993819-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect - **Company:** Modern Technology Solutions, Inc. - **Location:** St. Louis, MO, United States - **Experience:** Expert - **Salary:** $9,000.0 - $10,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Cloud Foundry, Databases, Data Architecture, Data Discovery, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Synchronization, Distributed Data Store, Interoperability, Metadata, Metadata Standards, Scrum Methodology, Zero Trust Network Access, Enterprise Data Management, Digital Twin, Cloud Platform System, Delivery Pipeline, Multi-Cloud, Data Layers, Api Design, Data Pipelines, Devsecops - **Published:** August 8, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17862631?backUrl=%2Fcareer%2F17862631%2FData-Architect-Missouri-St-Louis ## About the Role *Bachelor's degree with 8+ years of experience in data architecture, data engineering, enterprise architecture, or related disciplines. *DoD Compliance:Desired to meet DoD 8140/8570 requirements for anIAM Level IIposition (Ex: ISC2 CISSP or Sec+). *Strong experience designing and implementing data models, ontologies, schemas, APIs, metadata frameworks and distributed data architectures. *Proven experience with relational, graph and time-series databases; metadata/cataloging systems; and enterprise modern ETL/ELT pipelines (Ex: Argo Workflows). *Experience working within Scrum or Agile development teams. Desired Qualifications: *Experience building data fabrics, data meshes or authoritative enterprise data layers. *Experience integrating data architecture with MBSE tools, EA tools and Digital Threads. *Strong background in pipeline automation, API design and multi-enclave data synchronization. *Prior experience serving as a trusted advisor to government technical leadership. *Ability to automate data discovery, metadata capture and artifact ingestion to assess current Digital Ecosystem state and inform ROI analysis. *Broader understanding of DEE tech stack including MBSE, MS&A environments, cloud-native platforms, DevSecOps pipelines and enterprise architecture modeling. ## Description *Leads the architecture, deployment, and sustainment of the Cloud Native Platform (CNP) powering Model-Based Systems Engineering (MBSE), enterprise data integration, Digital Threads, and future Digital Twin operations. *Build and mature a secure, federated, multi-cloud platform that enables enterprise-scale Digital Engineering workflows, authoritative data synchronization and Zero Trust enforcement across multiple enclaves. *Work closely with the tech lead, enterprise architect, DE/MBSE engineers, platform/cloud engineers, cyber team and mission engagement leads to ensure seamless interoperability, automated pipelines and lifecycle traceability across the DEE. *Define data models, schemas, metadata structures, APIs and data governance rules that turn distributed data into authoritative decision-grade assets. * Data Architecture Leadership: Serve as the enterprise lead for data architecture, governance, modeling, and integration shaping standards, structures, and pipelines that unify engineering data across the DEE * Manage a Team of Data Engineers: Lead and mentor data engineers to build, automate and scale the enterprise data layer, including relational, graph, time-series and metadata systems supporting Digital Threads and lifecycle analytics * Cross-Functional Collaboration: Partner with the tech lead, enterprise architect, DE/MBSE engineers, platform/cloud engineers, cyber teams and mission engagement leads to ensure the data layer supports enterprise models, Digital Threads and operational workflows. * Strategic Advisory: Advise the Chief Architect and senior leaders on the maturity, gaps, risks and opportunities within NGA's data ecosystems, providing recommendations that enhance interoperability, automation and authoritative data synchronization. * Enterprise Data Modeling & Integration: Design end-to-end data models, schemas, ontologies, metadata structures, and APIs that enable a robust, scalable data layer integrating requirements, models, MS&A outputs, cost, schedule, test, and mission data. * Digital Thread Development: Collaborate with MBSE, platform, and application teams to build automated pipelines and interfaces that aggregate authoritative sources, ensure data fidelity, and maintain lifecycle traceability across tools and enclaves. * Data Governance: Establish and enforce enterprise-wide data governance including model integrity, data consistency, metadata standards, schema management, ontology alignment and lifecycle traceability. This ensures the DEE maintains an authoritative data source and supports secure, federated data synchronization across programs and TS/SCI boundaries * Vendor Engagement: Act as a key technical liaison between the government and multiple vendors, facilitating technical exchange meetings, resolving data integration issues and driving convergence toward vendor-agnostic, standards-based solutions. ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [DevSecOps: Injecting Security into Mobile CI/CD Pipelines](https://www.wearedevelopers.com/videos/273-devsecops-injecting-security-into-mobile-ci-cd-pipelines) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Why Event-Driven Architecture Isn’t About Speed (and When You Actually Need It)](https://www.wearedevelopers.com/magazine/745-why-event-driven-architecture-isn-t-about-speed-and-when-you-actually-need-it) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)