Data Engineer

Requisition Id 16994 

Overview:

The Geospatial Science & Engineering Division (GSED), of the National Security Sciences Directorate (NSSD), is seeking a highly motivated Data Engineer to support the automation of image processing and data science workflows in a classified environment. This position will contribute to the development of scalable analytic pipelines, automated exploitation tools, and reproducible computational workflows that improve the processing, integration, and interpretation of imagery, geospatial, and operational datasets. 

The successful candidate will assess research and operational needs and develop more complex data science solutions that advance organizational objectives. This role will conduct sophisticated analyses, integrate methodologies, and interpret outcomes to support innovation and improve efficiency. The selected individual will define systems and processes that enhance accuracy, scalability, security, and reproducibility of results across projects. 

This position requires a strong background in image processing, data engineering, workflow automation, geospatial data systems, and applied analytics, along with experience working in secure mission environments. The ideal candidate will be capable of translating complex datasets into actionable insights through dashboards, reports, technical artifacts, and user-facing tools, while supporting both research and operational objectives. 

Major Duties/Responsibilities:

• Develop and automate image processing and data science workflows that support mission-driven analysis in classified environments. 
• Design, implement, and maintain scalable pipelines for ingesting, cleaning, transforming, integrating, and analyzing imagery, geospatial, and structured operational data. 
• Assess data science project requirements and determine appropriate methods, tools, and technologies for workflow automation, image exploitation, and analytic delivery. 
• Define systems and processes that ensure data integrity, scalability, auditability, and reproducibility of results across projects. 
• Build and optimize data models, schemas, and databases that improve data quality, usability, and interoperability across systems. 
• Support the automation of preprocessing, feature extraction, metadata exploitation, validation, and quality control for image and geospatial datasets. 
• Deliver project results and confer with peers and stakeholders to ensure alignment with research, operational, and sponsor objectives. 
• Contribute to dashboards, technical documentation, reports, software prototypes, briefings, and other artifacts that communicate methods and findings.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• BS degree in computer science or a related field, and two years of relevant experience data science, image processing, geospatial analysis, data engineering, software engineering, or a related field. An equivalent combination of education and experience may be considered.
• Demonstrated experience designing and implementing end-to-end data systems or automated analytical workflows. 
• Experience processing and analyzing large, complex datasets, including imagery, geospatial data, and operational or mission-relevant data sources. 
• Experience with Python, SQL, and common libraries/frameworks for data analysis, workflow automation, and image or geospatial data processing. 
• Experience with relational databases, data modeling, ETL pipelines, and data wrangling to support scalable and reliable analytical workflows. 
• Experience translating analytical outputs into dashboards, reports, visualizations, or briefings for technical and non-technical stakeholders. 
• Demonstrated ability to develop and apply data science methods to improve efficiency, accessibility, and decision-making. 
• Experience working in secure or classified environments with strong attention to compliance, auditability, and proper data handling practices. 
• Strong written and oral communication skills and the ability to collaborate effectively on multidisciplinary teams. 
• Ability to work independently, plan and arrange own work, and coordinate with management to prioritize projects. 

Preferred Qualifications: 

• BS degree in data science, computer science, geospatial science, remote sensing, engineering, applied mathematics, or a related discipline. 
• Experience with image processing, imagery analysis, computer vision, or geospatial exploitation workflows involving satellite imagery, full-motion video, or related sensor data. 
• Experience with ArcGIS Pro, ArcGIS Enterprise, PostGIS, GeoPandas, or other geospatial analytics and visualization tools. 
• Experience developing natural language interfaces, retrieval-augmented generation systems, or other AI-enabled tools that improve access to structured or unstructured data. 
• Experience with machine learning, artificial intelligence, and/or natural language processing applied to operational or analytical workflows. 
• Experience operating LLM or AI workflows in secure or air-gapped environments. 
• Experience building guardrails, validation mechanisms, and controlled execution workflows for automated analytic systems. 
• Experience with Docker, Linux, cloud platforms, or other technologies supporting deployment and reproducible software workflows. 
• Experience coaching team members in technical skill development and promoting proper data practices.
• Certification in data science, machine learning, geospatial analysis, or a related field. 

Special Requirements: 

• Visa sponsorship is not available for this position. 
• Active TS//SCI clearance required at time of hire. 
• This position requires work on-site in secure facilities and may not be eligible for remote work.

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation. 

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience. 

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. 

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.