What are the responsibilities and job description for the Data Architect SME (Top Secret clearance required) position at Integration Innovation, Inc.?
Data Architect SME
Top Secret Required
Location: Chantilly, VA on site
Bachelors required
Minimum 10 years experience
The Data Architect (SME) leads the design and management of the organization's enterprise data environment, ensuring information is accurate, connected, and ready to support advanced analytics and AI. This role brings together traditional databases, modern data platforms, and semantic/knowledge-graph technologies to help teams access meaningful insights and power smarter decision-making. The SME also sets data standards, ensures secure data sharing across environments, and collaborates closely with engineering and AI teams to keep data structured, governed, and high quality.
Key Responsibilities
Design and maintain enterprise data architectures that integrate multiple data systems.
Build and manage knowledge graphs, ontologies, and metadata structures that improve data context and discovery.
Develop secure, well governed data pipelines and processes for high quality, trusted data.
Support AI and analytics teams by providing structured, contextual data for model development and retrieval workflows.
Establish data governance, data quality, and metadata standards across the organization.
Evaluate new technologies and recommend improvements to data platforms and processes.
Ensure data sharing and access follow security, compliance, and zero trust requirements.
Required Qualifications
10 years of experience
Data architecture, data engineering, or related areas.
Strong experience with enterprise data platforms, distributed systems, and modern data pipelines.
Familiarity with semantic technologies (RDF, OWL, SPARQL), ontologies, and knowledge graph design.
Experience with metadata management, data lineage, and data governance processes.
Knowledge of cloud data services and secure, multi environment data integrations.
Ability to communicate complex technical concepts clearly to non technical stakeholders.
Unique Skills / Technical Requirements
In-house custom developed application
Advanced AI, GenAI & Multi-Model Engineering
o Multi-model and multi-modality orchestration (reasoning, perception, memory, tool
execution)
o Temporal, spatial, geographic, quantitative, and computer vision AI implementation
o Named Entity Recognition (NER), contextual entity extraction, and resolution
o Multi-step retrieval and structured output generation
o Complex data parsing and streamlined ingestion
o Deep source citation and traceable analytic outputs
Data Architecture & ETL
o Vector, graph, and multi database orchestration
o Automated ETL pipeline creation, scheduling, and optimization
o Attribute Based Access Control (ABAC) at the data layer
o Provenance and end to end data lineage tracking
o Schema aligned ingestion and normalization of diverse structured and unstructured
data
Enterprise Infrastructure & CrossDomain Solutions
o Air gapped, hybrid, and on premise operational environments
o Container orchestration and distributed systems management (Kubernetes)
o Locally hosted GPU servers and hyperconverged nodes
o Multitenant CrossDomain Solutions (CDS)
Application Development & Integration
o UI, backend, and middleware engineering (TypeScript, React, Python, FastAPI,
LanceDB, lance graph, PostgreSQL, Temporal.io, Docker, Kubernetes)
o Integration of reasoning components, retrieval systems, databases, and AI / GenAI
services
o Use of modern programming languages and frameworks
Preferred Qualifications
Experience supporting AI/ML teams, retrieval architectures, or vector-based search.
Background working in secure, multi enclave, or zero trust environments.
Experience with streaming data, real time processing, or hybrid cloud architectures.
Advanced degree in Computer Science, Information Science, Data Engineering, or related field.
Top Secret Required
Location: Chantilly, VA on site
Bachelors required
Minimum 10 years experience
The Data Architect (SME) leads the design and management of the organization's enterprise data environment, ensuring information is accurate, connected, and ready to support advanced analytics and AI. This role brings together traditional databases, modern data platforms, and semantic/knowledge-graph technologies to help teams access meaningful insights and power smarter decision-making. The SME also sets data standards, ensures secure data sharing across environments, and collaborates closely with engineering and AI teams to keep data structured, governed, and high quality.
Key Responsibilities
Design and maintain enterprise data architectures that integrate multiple data systems.
Build and manage knowledge graphs, ontologies, and metadata structures that improve data context and discovery.
Develop secure, well governed data pipelines and processes for high quality, trusted data.
Support AI and analytics teams by providing structured, contextual data for model development and retrieval workflows.
Establish data governance, data quality, and metadata standards across the organization.
Evaluate new technologies and recommend improvements to data platforms and processes.
Ensure data sharing and access follow security, compliance, and zero trust requirements.
Required Qualifications
10 years of experience
Data architecture, data engineering, or related areas.
Strong experience with enterprise data platforms, distributed systems, and modern data pipelines.
Familiarity with semantic technologies (RDF, OWL, SPARQL), ontologies, and knowledge graph design.
Experience with metadata management, data lineage, and data governance processes.
Knowledge of cloud data services and secure, multi environment data integrations.
Ability to communicate complex technical concepts clearly to non technical stakeholders.
Unique Skills / Technical Requirements
In-house custom developed application
Advanced AI, GenAI & Multi-Model Engineering
o Multi-model and multi-modality orchestration (reasoning, perception, memory, tool
execution)
o Temporal, spatial, geographic, quantitative, and computer vision AI implementation
o Named Entity Recognition (NER), contextual entity extraction, and resolution
o Multi-step retrieval and structured output generation
o Complex data parsing and streamlined ingestion
o Deep source citation and traceable analytic outputs
Data Architecture & ETL
o Vector, graph, and multi database orchestration
o Automated ETL pipeline creation, scheduling, and optimization
o Attribute Based Access Control (ABAC) at the data layer
o Provenance and end to end data lineage tracking
o Schema aligned ingestion and normalization of diverse structured and unstructured
data
Enterprise Infrastructure & CrossDomain Solutions
o Air gapped, hybrid, and on premise operational environments
o Container orchestration and distributed systems management (Kubernetes)
o Locally hosted GPU servers and hyperconverged nodes
o Multitenant CrossDomain Solutions (CDS)
Application Development & Integration
o UI, backend, and middleware engineering (TypeScript, React, Python, FastAPI,
LanceDB, lance graph, PostgreSQL, Temporal.io, Docker, Kubernetes)
o Integration of reasoning components, retrieval systems, databases, and AI / GenAI
services
o Use of modern programming languages and frameworks
Preferred Qualifications
Experience supporting AI/ML teams, retrieval architectures, or vector-based search.
Background working in secure, multi enclave, or zero trust environments.
Experience with streaming data, real time processing, or hybrid cloud architectures.
Advanced degree in Computer Science, Information Science, Data Engineering, or related field.