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Oak Ridge National Laboratory

Geospatial Data Engineer

Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States, 37830


Requisition Id13721

Level: TP02

Overview:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation's biggest problems. We have a dedicated and creative staff of over 6,000 people! Our vision for diversity, equity, inclusion, and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization, as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNL's broader mission to accelerate scientific discoveries and their translation into energy, environment, and security solutions for the nation.

We are seeking a Geospatial Data Engineer who will focus on geospatial data analysis research. This involves deriving insights from analyzing geospatial data for emergency response and preparedness, population modelling and risk and resiliency modelling. This position resides in the Geospatial Data Modelling (GDM) Group in the Human Dynamics (HD) Section, Geospatial Science and Human Security (GSHS) Division, National Security Sciences Directorate (NSSD), atORNL.

The Geospatial Data Engineer works with a team of innovative researchers, engineers, and technologists to develop the next generation technological solutions to enable true impact on critical national security missions through a team-based approach and commitment to excellence. This position supports a broad range of projects into the development of geospatial data, models, methods, and computational approaches using earth observation, measurement, statistics, surveys, and digital traces to provide insights into human activities and interactions with the environment, from local to global scales. This role also augments our expertise in actively researching and implementing methods in creating foundational data at scale using novel data mining and machine learning (ML) techniques.

Major Duties/Responsibilities:

Design, develop, and implementnew tools, methods, and algorithms that improve our ability to collect source data from publicly available sources Provide support for the development of authoritative datasets of critical infrastructures and evaluate database schemas and apply them to scientific output. Automate work tasks to include authoring, managing, and maintaining metadata in a variety of accepted standard formats. Collaborate with cross-functional teams to understand data requirements and deliver geospatial data in prescribed format. All team members deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace - in how we treat one another, work together, and measure success.

Basic Qualifications:

BS in computer science, geography, geographic information science, remote sensing, environmental engineering, natural sciences, or related field and two (2) years of relevant work experience. Proven experience with development and implementation of data pipelines for geospatial data acquisition, transformation, and integration. Experience with data wrangling and transformation, ensuring data cleanliness and readiness for integration into spatial data development workflows. Preferred Qualifications:

MS in computer science, geography, geographic information science, remote sensing, environmental engineering, natural sciences, or related field and three (3) years of relevant work experience. Experience with open source GIS software like QGIS, PostGIS and geospatial python libraries Experience in geospatial analysis, data interpretation, database management, and GIS software development tools. Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory. Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Proficient in data wrangling and transformation, ensuring data cleanliness and readiness for integration into spatial data development workflows. Experience with SQL and spatial SQL

Benefits at ORNL:

ORNL offers competitive pay and benefits programs to attract and retain dedicated 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 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.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov or call 1.866.963.9545.

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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.

Nearest Major Market:

Knoxville