Data Engineer (Senior)

Location: Chantilly, VA
Security Clearance: Active TS or higher [Required] Must be able to obtain CI Polygraph
Job Type: Full-Time
Target Salary Range*: $140,000 - $170,000

*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

The Data Engineer (Senior) supports advanced visual analytic applications by building secure data pipelines, designing and optimizing large relational databases, and enabling high-performance analysis of structured and semi-structured data.

This role improves data workflows, system performance, and secure data practices while supporting advanced AI/GenAI capabilities, multi-database architectures, cross-domain environments, and application integration. The Data Engineer (Senior) also mentors junior team members and contributes to cross-team engineering standards.

Data Processing and Analytics

• Develop data processing workflows and analytics supporting desktop and web-based visual analytic tools.
• Support large-scale relational data analysis using visualization technologies and high-performance computing.
• Improve data workflows, system performance, and analytical efficiency.
• Support processing of structured, semi-structured, and unstructured data.

Data Ingestion and Integration

• Build secure data ingestion pipelines using open-source, COTS, and GOTS technologies.
• Integrate new data systems with existing data warehouses.
• Develop and optimize complex data parsing and streamlined ingestion processes.
• Support schema-aligned ingestion and normalization of diverse structured and unstructured data.
• Improve system performance and functionality across integrated data environments.

Database Design and Security

• Design and optimize enterprise relational databases.
• Establish standards for database operations and security.
• Support vector, graph, relational, and multi-database architectures.
• Implement Attribute-Based Access Control at the data layer.
• Support provenance and end-to-end data lineage tracking.
• Contribute to system optimization and security posture improvements.

ETL and Data Architecture

• Design, create, schedule, and optimize automated ETL pipelines.
• Support data architecture involving vector, graph, and multi-database orchestration.
• Support data modeling, transformation, integration, and normalization.
• Maintain traceability across complex data processing workflows.

AI and GenAI Data Engineering

• Support multi-model and multi-modality orchestration involving reasoning, perception, memory, and tool execution.
• Support temporal, spatial, geographic, quantitative, and computer vision AI implementations.
• Support Named Entity Recognition, contextual entity extraction, and entity resolution.
• Support multi-step retrieval and structured output generation.
• Enable deep source citation and traceable analytic outputs.
• Integrate data platforms with reasoning components, retrieval systems, databases, and AI/GenAI services.

Enterprise Infrastructure and Cross-Domain Support

• Support air-gapped, hybrid, and on-premises operational environments.
• Support container orchestration and distributed systems management using Kubernetes.
• Support locally hosted GPU servers and hyperconverged nodes.
• Support multitenant Cross-Domain Solutions.

Application Development and Integration

• Support UI, backend, and middleware engineering using TypeScript, React, Python, FastAPI, LanceDB, Lance Graph, PostgreSQL, Temporal.io, Docker, and Kubernetes.
• Integrate data services with application, retrieval, and AI/GenAI components.
• Support solutions using modern programming languages and frameworks.

Mentorship and Cross-Team Standards

• Mentor junior team members.
• Contribute to cross-team engineering and data standards.
• Promote consistent approaches to data architecture, processing, security, and performance.

Education

• Bachelor’s degree. [Required]

Experience

• Minimum 8 years of experience in data engineering, database design, or related fields. [Required]
• Experience working with structured and semi-structured data and visualization technologies. [Required]
• Experience improving data workflows, performance, and security. [Required]

Skills

• Strong skills in relational database design, SQL, and ETL/ELT processing. [Required]
• Familiarity with high-performance computing and mixed-technology environments. [Required]
• Strong analytical, communication, and collaboration skills. [Required]

• 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.