Data Engineer

at  Oak Ridge National Laboratory

OVERVIEW:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, Oak Ridge 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 data engineer who will focus on data development research; specifically, to create highly accurate authoritative data from a variety of sources 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), at ORNL.
The 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 R&D projects into the development of data, models, methods and computational approaches usingEarth 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 techniques.

BASIC QUALIFICATIONS:

• BS in computer science, geography, geographical information science, remote sensing, environmental engineering, natural sciences, or related field with two (2) years of relevant work experience. An equivalent combination of education and experience may be considered.
• Demonstrated experience in one or more of the following:
• Python for data engineering tasks
• SQL and PostgreSQL
• Extract, transform, and load (ETL) processes
• Experience working with different data formats, data wrangling, and data conflation
• Experience extracting data from pdfs, word documents, and unstructured text data

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.
• Familiarity with machine learning techniques and applications
• Experience with database design, development, and management.
• Familiarity with creation and conversion of various vector and raster data formats using Python
• Familiarity with geospatial analysis, data interpretation, spatial database management, GIS software and remote sensing tools.
• Experience with the planning, coordinating, analysis, design, construction, and implementation of new functionality and modifications to various databases to enhance and support business processes and meet information needs.
• Excellent written and verbal communication
• Good interpersonal skills
• 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.
  Visa Sponsorship
  Visa sponsorship is not available for this position.

• Contribute to and lead the design, development, and implementation of new tools, methods, and algorithms to implement and improve end to end data pipelines.
• Develop new and innovative data conflation solutions.
• Develop new critical infrastructure datasets and evaluate database schemas and apply them to scientific output.
• Develop and design verification and validation tools and methods and creation of scalable solutions.
• Automate work tasks to include authoring, managing, and maintaining metadata in a variety of accepted standard formats.
• Build, review, and package final datasets into various schema prescribed by sponsor.
  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.