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The Computational Urban Sciences Group in the Advanced Computing Methods for Engineered Systems Section of the Computational Science and Engineering Division seeks to hire a Data Engineer to serve in a role that focuses on large-scale urban informatics and engineering including but not limited to the design and development of tools for urban infrastructure modeling, optimization, and simulation. The Computational Urban Sciences Group is highly multi-disciplinary and the engagement is expected to expose the candidate to a variety of scientific domains such as urban health, urban disasters in the context of weather and climate, urban networks in the context of power grid, transportation, waterways, and supply chain supernetworks while building up from core computing application areas that include big-data, machine learning, network theory, intelligent visual analytics, high-performance computing, and distributed computing.


Major Duties/Responsibilities:


  • Planning, managing, controlling and data processing on assigned projects.
  • Mobilizing and leading the data track of projects with a focus on common deliverables, goals and timelines.
  • Developing high-scale, robust data sets with special focus on the state-of-the-art solutions for urban systems.
  • Interfacing with research teams to understand data needs and providing subject matter expertise.
  • Communicating specifics about the data models, query optimizations, and schema interpretation to research teams, and other team members
  • Designing, building and launching new data/study marts for the major national research programs.
  • Designing, building and launching new data quality, data extraction, transformation and loading processes.
  • Designing and developing architectures for intake, curation, organization, and dissemination of data in support of data science and related disciplines.
  • • Designing and development of high-performance database architectures.
  • Researching and evaluating the state-of-the-art data and information management technologies.
  • Working on a variety of data assignments; collaborate with scientists and engineers, and expect to produce reliable data products and systems.
  • Work in secure enclaves and open computing environments on a wide variety of applied areas.
  • Managing version control systems (Git and data archiving)


Basic Qualifications:


  • B.S. or M.S degree in Engineering, Computer Science, Information Systems, or closely related field.


Preferred Qualifications:


  • Prior experience working with healthcare data
  • Familiarity with Big Data (structured and unstructured datasets)
  • Demonstrated experience with collecting, organizing, storing, and preparing data analysis analyses
  • Ability to conduct tasks independently and communicate effectively to team members and stakeholders
  • Experience with version control systems (Git)
  • Ability to work on multiple projects at any given time
  • Experience with heath care informatics, and clinical data is highly desired
  • Ability to communicate and work on diverse and interdisciplinary teams.



ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also provided for convenience.

Other benefits include: 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.

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.