Active Top-Secret clearance with capability to obtain SCI/CI Poly if needed.
Bachelor's degree in Computer Science, IT, Engineering, or related field; advanced degree preferred.
Minimum 10 years of relevant professional experience.
Strong experience with enterprise data platforms and modern data pipelines.
Familiarity with semantic technologies and knowledge graph design.
Responsibilities
Design and maintain enterprise data architectures integrating multiple systems.
Build and manage knowledge graphs and metadata structures for improved data context.
Develop secure, governed data pipelines for high-quality data.
Support AI and analytics teams with structured data for model development.
Establish data governance and quality standards across the organization.
Evaluate new technologies and recommend improvements to data processes.
Ensure data sharing complies with security and zero trust requirements.
Benefits
Company-subsidized medical premiums for employees and dependents.
Dental and vision coverage.
401k retirement savings plan with up to 4% match.
Health Savings Account (HSA), FSA, and DCFSA options.
Company-paid short/long-term disability and life insurance.
Generous paid time off and all 11 federal holidays.
Legal and identity protection services.
Bonuses for certifications and reimbursement for related expenses.
Employee perks including company outings and discounts on services.
Full Job Description
PID: 26-22-10-012
Summary
E-INFOSOL LLC is seeking a motivated and results-driven Data Architect with 10 years of relevant professional experience in the cleared IT government contracting space to join our growing team.
Position Overview
The Data Architect will lead 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 Data Architect 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.
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
Active Top-Secret clearance with capability to obtain SCI/CI Poly if needed to meet contract requirements.
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline (or equivalent experience). Advanced degree in Computer Science, Information Science, Data Engineering, or related field preferred.
Minimum 10 years of relevant professional experience
Required Skills
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.
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.
Desired Skills:
In-house custom developed application
Advanced AI, GenAI & Multi-Model Engineering
Multi-model and multi-modality orchestration (reasoning, perception, memory, tool execution)
Temporal, spatial, geographic, quantitative, and computer vision AI implementation
Named Entity Recognition (NER), contextual entity extraction, and resolution
Multi-step retrieval and structured output generation
Complex data parsing and streamlined ingestion
Deep source citation and traceable analytic outputs
Data Architecture & ETL
Vector, graph, and multi database orchestration
Automated ETL pipeline creation, scheduling, and optimization
Attribute Based Access Control (ABAC) at the data layer
Provenance and end to end data lineage tracking
Schema aligned ingestion and normalization of diverse structured and unstructured data
Enterprise Infrastructure & CrossDomain Solutions
Air gapped, hybrid, and on premise operational environments
Container orchestration and distributed systems management (Kubernetes)
Locally hosted GPU servers and hyperconverged nodes
