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Closure Tech

Geospatial Data Systems Engineer

Data Management +1Confirmed live in the last 24 hours
Full-timeMcLean, VA, USANo salary listed

About the Job

Requirements

  • A bachelor's degree in Geography, GIS, Computer Science, Data Science, Engineering, or a related technical discipline.
  • At least 8 years of professional experience in geospatial technology, software development, data engineering, data analysis, or a related technical field.
  • An active TS/SCI security clearance with polygraph.
  • Strong Python experience for geospatial data processing, automation, transformation, analysis, and workflow improvement.
  • Demonstrated experience working with large geospatial datasets, including cleaning, formatting, joining, enriching, validating, and preparing data for analysis or publication.
  • Hands-on experience with ArcGIS Enterprise, ArcGIS Portal, or ArcGIS Online, including publishing and maintaining hosted feature layers, web maps, dashboards, and geospatial content.
  • Experience curating geospatial data holdings, including organizing datasets, maintaining metadata, improving discoverability, and ensuring data quality.
  • Experience developing dashboards, reports, or analytic visualizations in Tableau or a comparable business intelligence platform.
  • Understanding of geospatial data formats, projections, coordinate systems, spatial joins, geoprocessing workflows, cartographic principles, and spatial data management.
  • Experience with relational databases, preferably PostgreSQL/PostGIS, for storing, querying, and managing spatial or tabular data.
  • Ability to work independently with minimal guidance while coordinating across teams, offices, and mission stakeholders.

Responsibilities

  • Partner with mission users to understand geospatial data needs, analytic questions, visualization requirements, and operational workflows.
  • Identify, acquire, clean, transform, validate, curate, and publish large geospatial and tabular datasets from diverse sources.
  • Develop Python scripts and tools to automate geospatial data processing, quality control, enrichment, transformation, and publication workflows.
  • Manage and update ArcGIS Portal content, including hosted feature layers, map services, web maps, dashboards, data hubs, and related geospatial products.
  • Build and maintain Tableau dashboards, reports, and analytic visualizations used by the data processing office and mission stakeholders.
  • Apply cartographic design, symbology, labeling, layer management, metadata practices, and performance tuning to improve the usability of geospatial products.
  • Integrate structured, unstructured, tabular, and spatial datasets into cohesive analytical and visualization environments.
  • Support geospatial data library functions, including dataset organization, metadata creation, version management, quality control, discoverability, and lifecycle maintenance.
  • Develop documentation, data dictionaries, standard operating procedures, user guidance, and technical recommendations that support repeatable data management and visualization workflows.
  • Work independently across two office environments while collaborating with multidisciplinary teams and communicating technical concepts to technical and non-technical audiences.

Desired Qualifications

  • Advanced Tableau experience, including dashboard development, calculated fields, filters, data preparation, publishing, and maintaining products for operational users.
  • Experience with ArcGIS Pro, ArcPy, GeoPandas, Shapely, Fiona, Rasterio, GDAL, QGIS, or similar geospatial tools and libraries.
  • Experience building repeatable data pipelines for geospatial data ingestion, processing, validation, and publication.
  • Experience with cloud-hosted datasets, Amazon S3, ArcGIS Hub-style environments, or secure integrations between enterprise data repositories and ArcGIS Portal.
  • Experience with PostgreSQL/PostGIS performance tuning, spatial indexing, and geospatial query optimization.
  • Experience with Elasticsearch, Kibana, or similar search, analytics, and visualization tools.
  • Familiarity with data governance, data stewardship, metadata standards, data quality, Agile practices, Jira, Confluence, DevOps principles, version control, or containerized workflows.
  • Background in spatial statistics, predictive analytics, machine learning, or advanced geospatial modeling.

About the Company

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