Data Architect

E-Infosol LLC•Washington, DC

8h•$177,000 - $187,000

About The Position

E-INFOSOL LLC is seeking a motivated, results-driven Data Architect with 10 years of relevant professional experience in the cleared IT government contracting space. 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. The role integrates traditional databases, modern data platforms, and semantic and knowledge-graph technologies to help teams access insights and make informed decisions. It also establishes data standards, supports secure data sharing across environments, and works closely with engineering and AI teams to keep data structured, governed, and high quality. E-INFOSOL is a Service Disabled Veteran Owned Small Business in the Washington, D.C. metropolitan area. It develops tailored solutions for customers and provides expertise in cloud computing, virtualization, cybersecurity, software development, and data services. Its customers include the Intelligence Community, Department of Defense, Federal Law Enforcement, civilian agencies, and the private sector. The company describes itself as people-first, with a focus on employee culture and career growth. It offers certification-related bonuses and reimbursement. E-INFOSOL provides equal employment opportunities and prohibits discrimination and harassment in accordance with applicable laws.

Requirements

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.
Minimum 10 years of relevant professional experience.
Experience in 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.

Nice To Haves

Advanced degree in Computer Science, Information Science, Data Engineering, or a related field.
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.
In-house custom-developed application experience.
Advanced AI, GenAI, and multi-model engineering; multi-model and multimodality orchestration involving reasoning, perception, memory, and tool execution.
Experience implementing temporal, spatial, geographic, quantitative, and computer vision AI.
Experience with named entity recognition (NER), contextual entity extraction, and resolution.
Experience with multi-step retrieval, structured output generation, complex data parsing, streamlined ingestion, deep source citation, and traceable analytic outputs.
Experience with data architecture and ETL, vector, graph, and multi-database orchestration, and automated ETL pipeline creation, scheduling, and optimization.
Experience with attribute-based access control (ABAC) at the data layer, provenance, end-to-end data lineage tracking, and schema-aligned ingestion and normalization of diverse structured and unstructured data.
Experience with air-gapped, hybrid, and on-premise operational environments; Kubernetes and distributed systems management; locally hosted GPU servers and hyperconverged nodes; and multitenant CrossDomain Solutions (CDS).
UI, backend, and middleware engineering experience with TypeScript, React, Python, FastAPI, LanceDB, lance graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.
Experience integrating reasoning components, retrieval systems, databases, and AI/GenAI services, and using modern programming languages and frameworks.

Responsibilities

Design and maintain enterprise data architectures that integrate multiple data systems.
Build and manage knowledge graphs, ontologies, and metadata structures to 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.

Benefits

Company-subsidized medical premiums, including family and dependent options.
Dental insurance.
Vision insurance.
Retirement savings plan with up to a 4% 401(k) match.
Health Savings Account (HSA), Flexible Spending Account (FSA), and Dependent Care Flexible Spending Account (DCFSA).
Company-paid short- and long-term disability coverage, with additional supplemental options.
Company-paid life and AD&D insurance, with additional supplemental options.
Generous paid time off and all 11 federal holidays.
Legal and identity protection services.
Bonuses and reimbursement for certifications.
Uber One, company outings, and discounts on services including pet insurance.