This Senior Data Engineering role supports federal civilian agencies by converting data into measurable outcomes. The position is centered on building and operating secure data infrastructure for chatbot and AI-powered applications, including PostgreSQL-based services, ETL/ELT pipelines, enterprise integration, and containerized deployment in controlled environments requiring a SECRET clearance.

Location

Sterling, VA (onsite)

Salary

USD 153,000 - 207,000 per year

Role Responsibilities

Design, develop, and maintain the data infrastructure that supports the chatbot and related AI-powered applications.
Manage and optimize PostgreSQL databases, including use of pgvector for vector similarity search.
Build and maintain data ingestion pipelines for structured, semi-structured, and unstructured data.
Integrate document processing technologies such as Docling and Tesseract into automated pipeline workflows.
Support document metadata extraction, transformation, validation, indexing, and storage.
Partner with AI/ML engineers to improve data retrieval, embedding storage, and RAG workflows.
Create Python-based services, scripts, and APIs to move data between systems.
Assist with migrating database services and supporting components into Podman containers.
Improve reliability, performance, observability, and backup and recoverability for database services.
Troubleshoot data integration issues across application services, databases, and AI inference systems.
Evaluate and help design an enterprise data fabric architecture.
Develop reusable data pipelines and integration patterns to support 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 approaches.
Define and implement data quality, consistency, validation, and governance controls.
Work with enterprise architects and stakeholders to identify integration requirements and technical solutions.
Help establish common data models, integration standards, and reusable data services.
Assess open-source and commercial data integration technologies for use in secure government environments.
Plan and execute data migrations between legacy systems, modern databases, and enterprise applications, including mapping, transformation, validation, and reconciliation.
Develop ETL/ELT pipelines using Python, SQL, and appropriate data integration frameworks.
Perform extraction, transformation, cleansing, mapping, reconciliation, and validation tasks.
Support migration testing, performance optimization, rollback planning, and post-migration verification.
Develop scripts and automation to streamline recurring migration activities and produce technical documentation, migration plans, mapping specifications, and operational procedures.
Implement and support containerized data services using Podman and container orchestration tools.
Support applications and databases running on Red Hat Enterprise Linux and Windows Server.
Automate database deployment, configuration, monitoring, and maintenance activities.
Implement secure data access controls, encryption, audit logging, and data handling practices, including support for air-gapped and classified environments.
Collaborate with cybersecurity and infrastructure teams to ensure compliance with applicable federal security requirements.
Participate in vulnerability remediation, software evaluation, change management, and accreditation support activities.
Implement monitoring and operational logging solutions using tools such as Splunk.

Required Qualifications

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, database schema design, and performance tuning.
Experience administering, developing against, or optimizing PostgreSQL or comparable enterprise relational database systems.
Demonstrated experience designing and implementing ETL/ELT pipelines.
Experience with enterprise data migrations, including data mapping, transformation, validation, and reconciliation.
Familiarity with REST APIs and JSON, including 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, automated testing, and modern software development practices.
Ability to design, document, and troubleshoot complex data workflows.
Strong communication skills and ability to collaborate across multidisciplinary engineering teams.

Clearance Requirement

SECRET

Key Skills for Success

Artificial Intelligence (AI)
Data Solutions
Technical Solutions

Technologies

PostgreSQL, pgvector, Python, SQL, Docling, Tesseract, Podman, Red Hat Enterprise Linux, Windows Server, Linux, REST APIs, JSON, Git, Splunk, Podman containers, ETL/ELT, RAG, vector databases, Retrieval-Augmented Generation (RAG), embedding storage, data ingestion pipelines, 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

Work Requirements

Years of Experience: 10+ years of related experience (may vary based on technical training, certification(s), or degree)
Travel Required: Less than 10%
Citizenship: U.S. Citizenship Required

Education

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field.

Senior Data Engineer

Job Description