Data Engineer

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Full Time Chantilly, VA, US

Salary Range: $ To $ Annually

E-INFOSOL LLC is seeking a motivated and results-driven Data Engineer with 8 years of relevant professional experience in the cleared IT government contracting space to join our growing team.

The Data Engineer will support advanced visual analytic applications by building data pipelines, designing large relational databases, and enabling high‑performance analysis across structured and semi‑structured data. This role helps streamline processes, improve system performance, and strengthen secure data practices while mentoring junior team members and contributing to cross‑team standards.

• Develop data processing workflows and analytics for desktop and web‑based visual analytic tools.
• Support large‑scale relational data analysis using visualization and high‑performance computing.
• Build secure data ingest pipelines using open‑source, COTS, and GOTS technologies.
• Design and optimize enterprise relational databases and establish standards for operations and security.
• Integrate new data systems with existing data warehouses and improve performance and functionality.
• Provide mentorship and contribute to system optimization and secure posture improvements.

• 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 8 years of relevant professional experience in data engineering, database design, or related fields.

• Strong skills in relational database design, SQL, and ETL/ELT processing.
• Experience working with structured and semi‑structured data and visualization technologies.
• Familiarity with high‑performance computing and mixed‑technology environments.
• Strong analytical, communication, and collaboration skills.
• Experience improving data workflows, performance, and security.

• Experience supporting federal or secure, multi‑enclave environments.
• Background with advanced visualization platforms or high‑volume data processing.
• Knowledge of data modeling, warehousing, and performance tuning.

• 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
• 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 & Cross Domain Solutions
• Air gapped, hybrid, and on premise operational environments
• Container orchestration and distributed systems management (Kubernetes)
• Locally hosted GPU servers and hyperconverged nodes
• Multitenant Cross Domain Solutions (CDS)
• Application Development & Integration
• UI, backend, and middleware engineering (Type Script, React, Python, FastAPI, LanceDB, lance graph, PostgreSQL, Temporal.io, Docker, Kubernetes)
• Integration of reasoning components, retrieval systems, databases, and AI / GenAI services
• Use of modern programming…