Senior Digital Data Architect

Senior Digital Data Architect

MTSI is seeking a Senior Digital Data Architect to lead the design, implementation, and evolution of a Canonical Data Model (CDM) that integrates structured, semi-structured, and model-based data sources. The ideal candidate has a proven track record of architecting and managing enterprise-scale data systems, building robust ETL frameworks, and deploying data access interfaces that support knowledge discovery across diverse domains.

This role requires a strategic thinker who can balance technical execution with architectural foresight, guiding teams and shaping data standards that enable interoperability across systems engineering and analytical workflows.

Location: In person at Mark Center, Alexandria, VA/Hybrid (TBD)

Employment Type: Full-Time

Key Responsibilities Architect and Oversee the Ontology/Canonical Data Model (CDM):

• Lead the end-to-end design of a scalable CDM using Python and Pydantic.
• Define modeling standards, governance, and interoperability strategies across structured (tabular), unstructured (JSON/API), and MBSE (SysML, LML) data sources.
• Establish versioning, change control, and extensibility practices for CDM evolution.
• Help define unified ontology for system of system architecture.

Lead ETL Architecture and Data Integration:

• Architect and manage ETL pipelines integrating data from multiple enterprise systems.
• Oversee data quality, lineage, and validation standards using tools like Pandera.
• Design for scalability, automation, and operational monitoring.

Database and Storage Strategy:

• Define storage architectures using No
  
  SQL (Mongo
  
  DB, Dynamo
  
  DB) and graph databases (Neo4j).
• Optimize database design for query performance and relationship-heavy data.
• Guide decisions on indexing, caching, and hybrid storage strategies.

Web Interface and API Enablement:

• Direct the design and development of a web interface for querying and managing CDM data.
• Lead integration of backend APIs (FastAPI/Django) and front-end frameworks (React/Next.js).
• Promote best practices in RESTful and Graph
  
  QL API design.

Model Orchestration and Integration:

• Lead the integration of the CDM with model orchestration tools such as Ansys Model Center, or open-source alternatives.
• Develop frameworks for orchestrating analytical flows, simulation models, and design studies using standardized interfaces.
• Ensure interoperability between MBSE environments, analytical models, and enterprise data repositories.
• Collaborate with systems engineers to implement automated data flows and traceability between system models and analytical results.
• Support model execution pipelines and configuration management across engineering tools and simulation environments.

Digital Data Leadership:

• Develop and champion enterprise and digital data strategies.
• Align data structures with ontologies and semantic modeling standards (RDF, OWL).
• Mentor teams on data architecture principles and reusable data design.

Collaboration & Mentorship:

• Serve as the technical authority across cross-functional teams.
• Mentor mid-level engineers in data modeling, ETL design, and data quality practices.
• Ensure solutions align with organizational architecture and compliance standards.
• Using tools such as Git, Git Hub, or Git Lab to maintain high code quality and consistency.
• Support the setup, configuration, and maintenance of CI/CD pipelines (e.g., Git Hub Actions, Jenkins, Azure Dev Ops, or Git Lab CI) to automate testing, deployment, and integration processes.
• Utilize collaboration tools like Confluence, Jira, and SharePoint to manage tasking and documentation.

Required Qualifications

• Education:
  
  Bachelor's or Master's in Computer Science, Data Science, Systems Engineering, or related field.

Experience

• 5+ years in software development, data architecture, or enterprise data systems.
• Proven leadership in designing and deploying large-scale data systems.
• Strong experience architecting ETL frameworks and managing production data pipelines.
• Deep proficiency with Python, Pydantic, FastAPI/Flask/Django, No
  
  SQL (Mongo
  
  DB), and Neo4j.
• Understanding of MBSE concepts (SysML,UAF) and semantic data modeling.

Technical Leadership

• Expertise in systems integration, version-controlled data…