Senior Geospatial Data Engineer

In this Senior Geospatial Data Engineer role, you will support mission geospatial data curation, ArcGIS Portal visualization, and data processing and analytics. The position emphasizes large-scale dataset preparation, automated geospatial workflows, and dashboard reporting using Python and Tableau.

Location

McLean, VA (onsite)

Compensation

USD 137,000 - 200,200 per yearly

Pay transparency details for the Washington, DC metropolitan area list a base pay range of $137,000.00 - $182,000.00 - $200,200.00 annually. For other states, geographic cost of labor is used to determine market-driven ranges, which may differ by location.

Role Responsibilities

• Manage, curate, publish, and maintain geospatial datasets, hosted feature layers, web maps, dashboards, and data products in ArcGIS Portal.
• Ensure mission users have access to accurate, well-organized, current, and usable geospatial information.
• Use Python, Tableau, ArcGIS, and related tools to process large datasets, automate workflows, prepare data for analysis, and produce visual analytics that highlight patterns, trends, anomalies, and operationally relevant insights.
• 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 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 for the data processing office and mission stakeholders.
• Apply cartographic design practices, symbology, labeling, layer management, metadata practices, and performance tuning to improve geospatial product usability.
• Integrate structured, unstructured, tabular, and spatial datasets into cohesive analytical and visualization environments.
• Support geospatial data library functions such as dataset organization, metadata creation, version management, quality control, discoverability, and lifecycle maintenance.
• Create documentation, data dictionaries, standard operating procedures, user guidance, and technical recommendations to enable 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.

Required Qualifications

• Active TS/SCI security clearance with polygraph.
• U.S. Citizenship (required for eligibility).
• Bachelor’s degree in Geography, GIS, Computer Science, Data Science, Engineering, or a related technical discipline.
• 12+ years of professional experience in geospatial technology, software development, data engineering, data analysis, or a related technical field.
• Strong Python experience for geospatial data processing, automation, transformation, analysis, and workflow improvement.
• Demonstrated experience handling 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.
• Strong analytical, problem-solving, communication, and customer engagement skills.
• Ability to work independently with minimal guidance while coordinating effectively across teams, offices, and mission stakeholders.
• Employment for cleared roles is contingent upon verification of clearance status, and applicants who do not currently hold the required clearance will not be eligible for consideration.
• Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).

Technologies

Python, Tableau, ArcGIS, ArcGIS Enterprise, ArcGIS Portal, ArcGIS Online, ArcPy, GeoPandas, Shapely, Fiona, Rasterio, GDAL, QGIS, PostgreSQL, PostGIS, Elasticsearch, Kibana, Amazon S3, ArcGIS Hub, Jira, Confluence, DevOps

Benefits

• Robust 401(k) with company match
• Mental health resources
• Student loan repayment assistance
• Adoption reimbursement
• Pet insurance

Preferred 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.