Geospatial Data Architect (Hybrid Eligible)

About the role

We are seeking a Geospatial Data Architect who will focus on designing and governing data ecosystems that support spatial analytics, modeling, and operational workflows. This position resides in the Geoinformatics Engineering Group in the Human Dynamics Section, Geospatial Science and Engineering Division, National Security Sciences Directorate at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities

• Design and govern geospatial data architecture: Define scalable data models, storage patterns (e.g., Parquet/GeoParquet in object stores), and overall lakehouse/warehouse strategy to support spatial analytics and interoperability.
• Establish data standards, integration patterns, and lifecycle management: Oversee ingestion frameworks, metadata/cataloging (e.g., STAC), data versioning (e.g., DVC), and policy-driven management systems (e.g., iRODS, Globus), ensuring consistency, reproducibility, and accessibility.
• Optimize performance, scalability, and cross-team alignment: Implement efficient partitioning, indexing, and distributed processing strategies while coordinating with engineers and scientists to align infrastructure with geospatial workflows and analytical needs.

Basic Qualifications

• A BS or MS degree in Computer Science, Geospatial Science, Data Engineering, or related field
• A minimum of 5 years of experience in data architecture, engineering, or backend systems
• Strong understanding of data modeling (relational and non-relational)
• Experience with SQL and at least one major database system
• Familiarity with geospatial data types and tools (vector/raster concepts, GDAL, spatial indexing basics)

Preferred Qualifications

• Experience with Parquet and GeoParquet, including hive-partitioning, partitioning strategies, compression, and query optimization in object storage environments
• Hands-on experience designing data systems on S3 or S3-compatible object storage platforms
• Design and operate modern geospatial data platforms, with a strong understanding of data lake/lakehouse/warehouse tradeoffs and governance (access control, policy enforcement, lifecycle management, etc.)
• Build scalable processing pipelines for large raster/vector datasets using distributed compute and spatial analytics tooling (e.g., Spark/Dask/Flink, Sedona/BigQuery GIS, etc.)
• Work with cloud-native geospatial formats and core spatial concepts (CRSs, transformations, spatial indexing such as H3/S2, etc.)
• Implement data management best practices across the lifecycle: versioning and reproducibility, metadata/catalogs and lineage, and reliable transfer/sharing (e.g., DVC-like tooling, STAC-like standards, DataHub/Amundsen, Globus/iRODS, etc.)
• 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

Special Requirements

• Q clearance with SCI: This position requires the ability to obtain and maintain a Secret Compartmented Information (SCI) clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. In addition, due to the SCI, you may also be subject to random polygraph testing.
• Visa Sponsorship: Visa sponsorship is not available for this position.