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 (depending on education, experience, certifications, and position-specific requirements)

About the role

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.

Responsibilities

• 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.

Qualifications

• Education: Bachelor’s degree (required).
• Experience: Minimum 8 years 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).

Preferred Qualifications

• 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.