Senior Data Engineer

Build data infrastructure that turns information into measurable outcomes while supporting federal civilian agencies. This Senior Data Engineering role at General Dynamics Information Technology (GDIT) is onsite in Sterling, VA, combining enterprise data engineering with secure, containerized services and AI-powered application support. The position requires a SECRET clearance and offers a likely salary range of $153,000 - $207,000 per year.

What you will work on

You will design, develop, and maintain the data infrastructure behind a chatbot and related AI-powered applications. The work centers on relational databases, data pipelines (ETL/ELT), and enterprise data integration, including document-driven ingestion and modern migration efforts into containerized environments.

• Design and maintain data infrastructure supporting chatbot and AI-powered applications.
• Administer and optimize PostgreSQL, including use of the pgvector extension for vector similarity search.
• Build and maintain ingestion pipelines for structured, semi-structured, and unstructured data.
• Integrate document processing technologies such as Docling and Tesseract into automated pipelines.
• Handle document metadata extraction, transformation, validation, indexing, and storage.
• Partner with AI/ML engineers to optimize data retrieval, embedding storage, and RAG workflows.
• Create Python-based services, scripts, and APIs to move data between systems.
• Support migration of database services and components into Podman containers.
• Improve database reliability, performance, observability, backup procedures, and recoverability.
• Troubleshoot data integration issues across application services, databases, and AI inference systems.
• Evaluate and contribute to enterprise data fabric architecture and integration approaches.
• Define reusable data pipelines and integration patterns across multiple applications and business domains.
• Support enterprise data catalogs, metadata management, data lineage, and data discovery capabilities.
• Evaluate data virtualization, data federation, and distributed data access strategies.
• Implement data quality, consistency, validation, and governance controls.
• Assess and execute data migrations between legacy systems, modern databases, and enterprise applications, including mapping, transformation, validation, reconciliation, testing, rollback planning, and verification.
• Develop technical documentation, migration plans, data mapping specifications, and operational procedures.
• Support containerized data services using Podman and container orchestration tools, including deployments in air-gapped and classified environments.
• Automate database deployment, configuration, monitoring, and maintenance activities on Red Hat Enterprise Linux and Windows Server.
• Implement secure data access controls, encryption, audit logging, and data handling practices.
• Implement monitoring and operational logging solutions using tools such as Splunk.
• Collaborate with cybersecurity and infrastructure teams for compliance with applicable federal security requirements, including vulnerability remediation, change management, and accreditation support.

What you bring

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field, or equivalent practical experience.
• 7+ years of experience in data engineering, database development, data integration, or related software engineering disciplines.
• Strong proficiency in Python for data processing, scripting, automation, and service integration.
• Advanced SQL skills, including query optimization, schema design, and performance tuning.
• Experience administering, developing against, or optimizing PostgreSQL or comparable enterprise relational databases.
• Demonstrated experience designing and implementing ETL/ELT pipelines.
• Experience with enterprise data migrations, including mapping, transformation, validation, and reconciliation.
• Familiarity with REST APIs, JSON, and structured and semi-structured data formats.
• Experience with Linux administration, shell scripting, and deployment automation.
• Understanding of data modeling, relational databases, data integrity, and data lifecycle management.
• Experience with Git and automated testing, plus modern software development practices.
• Ability to design, document, and troubleshoot complex data workflows.
• Strong communication skills and ability to collaborate across multidisciplinary engineering teams.

Tools and technologies

PostgreSQL, pgvector, Python, SQL, Docling, Tesseract, Podman, Red Hat Enterprise Linux, Windows Server, REST APIs, JSON, Git, Splunk, ETL/ELT, RAG, embedding storage, Apache Tika, Redis, PgBouncer, Apache Airflow, Apache NiFi, Apache Kafka, data fabric, data mesh, data virtualization, data catalogs, data lineage, data governance frameworks, AWS, Azure, CI/CD.

Security and work requirements

• Clearance level: Secret
• Citizenship: U.S. Citizenship Required
• Travel: Less than 10%
• Years of experience: 10+ years of related experience (may vary based on technical training, certification(s), or degree)
• Location: Sterling, VA (onsite)