{"schemaVersion":"jobsearcher.job.v1","id":"e530fa52bc8d14577cbdb552","url":"https://jobsearcher.com/jobs/e530fa52bc8d14577cbdb552","canonicalUrl":"https://jobsearcher.com/jobs/e530fa52bc8d14577cbdb552","title":"Geospatial Data Engineer","description":"must be a local candidates based in California.I'm looking for an experienced Data Engineer with a strong geospatial background and expertise in AWS, Apache Sedona/GeoPandas, and PySpark.Location: California (100% Remote)Core ResponsibilitiesData Pipeline EngineeringDesign, develop, and maintain scalable AWS-native data pipelines using Python and PySpark.Build automated ingestion, transformation, and processing workflows for large geospatial and operational datasets.Optimize pipeline performance, scalability, and reliability.Remote Sensing & Raster Data ProcessingDevelop and support data pipelines for large raster-based datasets and satellite imagery.Manage multi-band imagery, including visible, near-infrared, and red-edge spectral bands.Implement selective and incremental ingestion strategies to efficiently process only relevant data subsets.Cloud Data ArchitectureDesign and maintain cloud-native geospatial data solutions within AWS.Support data lake, warehouse, and analytical platform initiatives.Geospatial ProcessingDevelop distributed geospatial processing solutions using Apache Sedona, GeoPandas, Shapely, and related technologies.Perform large-scale spatial analysis, joins, indexing, and optimization.Data Platform DevelopmentSupport modern data engineering practices including CI/CD, automated testing, version control, and Infrastructure as Code.Contribute to enterprise data governance and data quality initiatives.Agile CollaborationWork closely with Business Analysts, Product Owners, GIS Specialists, Data Scientists, and Engineering teams in an Agile environment.Participate in sprint planning, design reviews, and technical discussions.Required QualificationsEducationBachelor's degree in Computer Science, Engineering, GIS, Geography, Data Science, or a related field.Experience7+ years of Data Engineering experience designing and supporting enterprise-scale data pipelines.Technical RequirementsStrong proficiency with Python, PySpark, SQL, and Apache Sedona.Hands-on experience building geospatial and raster data processing solutions on AWS.Experience developing cloud-native ETL and data integration workflows.Strong understanding of coordinate reference systems, projections, and spatial transformations (WGS84, NAD83, EPSG standards).Geospatial TechnologiesExperience with Shapefile, GeoJSON, GeoParquet, GeoPackage, KML, GeoTIFF, and Cloud-Optimized GeoTIFF (COG).Experience processing large-scale raster datasets and satellite imagery.Expertise with raster-vector analysis and multi-band imagery processing.Understanding of vegetation, environmental, and remote sensing analytics workflows.Spatial AnalyticsSpatial indexing and partitioning techniques including R-Tree, QuadTree, and distributed spatial joins.Geometry operations including buffering, intersections, nearest-neighbor analysis, topology validation, and geometry simplification.Experience addressing performance optimization challenges for large spatial datasets.Data Engineering & OrchestrationExperience with Airflow, Dagster orchestration platforms. Knowledge of dimensional modeling, historical data management, and data warehousing concepts.Familiarity with CI/CD practices, automated testing, and Git-based development workflows.Nice to HaveExperience with Palantir Foundry.STAC or other satellite imagery cataloging standards.LiDAR datasets and processing workflows.Utility, energy, environmental, infrastructure, or asset management industry experience.Experience building geospatial machine learning or advanced analytics solutions.","company":"Hatch Pros","rawCompany":"hatch pros","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-09-24T07:01:42.662Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.02","title":"Geographic Information Systems Technologists and Technicians","slug":"geographic-information-systems-technologists-and-technicians"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541370","title":"Surveying and Mapping (except Geophysical) Services","slug":"surveying-and-mapping-except-geophysical-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541360","title":"Geophysical Surveying and Mapping Services","slug":"geophysical-surveying-and-mapping-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Geospatial Data Engineer","description":"must be a local candidates based in California.I'm looking for an experienced Data Engineer with a strong geospatial background and expertise in AWS, Apache Sedona/GeoPandas, and PySpark.Location: California (100% Remote)Core ResponsibilitiesData Pipeline EngineeringDesign, develop, and maintain scalable AWS-native data pipelines using Python and PySpark.Build automated ingestion, transformation, and processing workflows for large geospatial and operational datasets.Optimize pipeline performance, scalability, and reliability.Remote Sensing & Raster Data ProcessingDevelop and support data pipelines for large raster-based datasets and satellite imagery.Manage multi-band imagery, including visible, near-infrared, and red-edge spectral bands.Implement selective and incremental ingestion strategies to efficiently process only relevant data subsets.Cloud Data ArchitectureDesign and maintain cloud-native geospatial data solutions within AWS.Support data lake, warehouse, and analytical platform initiatives.Geospatial ProcessingDevelop distributed geospatial processing solutions using Apache Sedona, GeoPandas, Shapely, and related technologies.Perform large-scale spatial analysis, joins, indexing, and optimization.Data Platform DevelopmentSupport modern data engineering practices including CI/CD, automated testing, version control, and Infrastructure as Code.Contribute to enterprise data governance and data quality initiatives.Agile CollaborationWork closely with Business Analysts, Product Owners, GIS Specialists, Data Scientists, and Engineering teams in an Agile environment.Participate in sprint planning, design reviews, and technical discussions.Required QualificationsEducationBachelor's degree in Computer Science, Engineering, GIS, Geography, Data Science, or a related field.Experience7+ years of Data Engineering experience designing and supporting enterprise-scale data pipelines.Technical RequirementsStrong proficiency with Python, PySpark, SQL, and Apache Sedona.Hands-on experience building geospatial and raster data processing solutions on AWS.Experience developing cloud-native ETL and data integration workflows.Strong understanding of coordinate reference systems, projections, and spatial transformations (WGS84, NAD83, EPSG standards).Geospatial TechnologiesExperience with Shapefile, GeoJSON, GeoParquet, GeoPackage, KML, GeoTIFF, and Cloud-Optimized GeoTIFF (COG).Experience processing large-scale raster datasets and satellite imagery.Expertise with raster-vector analysis and multi-band imagery processing.Understanding of vegetation, environmental, and remote sensing analytics workflows.Spatial AnalyticsSpatial indexing and partitioning techniques including R-Tree, QuadTree, and distributed spatial joins.Geometry operations including buffering, intersections, nearest-neighbor analysis, topology validation, and geometry simplification.Experience addressing performance optimization challenges for large spatial datasets.Data Engineering & OrchestrationExperience with Airflow, Dagster orchestration platforms. Knowledge of dimensional modeling, historical data management, and data warehousing concepts.Familiarity with CI/CD practices, automated testing, and Git-based development workflows.Nice to HaveExperience with Palantir Foundry.STAC or other satellite imagery cataloging standards.LiDAR datasets and processing workflows.Utility, energy, environmental, infrastructure, or asset management industry experience.Experience building geospatial machine learning or advanced analytics solutions.","datePosted":"2026-09-24T07:01:42.662Z","dateModified":"2026-09-24T07:01:42.662Z","hiringOrganization":{"@type":"Organization","name":"Hatch Pros","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e530fa52bc8d14577cbdb552"},"url":"https://jobsearcher.com/jobs/e530fa52bc8d14577cbdb552"}}