GeoSpatial Data Engineer
Houston, TX
Contracted
Mid Level
Job Title: Big Data Engineer (GeoSpatial)
Location: Houston, TX
Duration:- 6-12 Months
Key Responsibilities
Requirements
Technical Skills
Location: Houston, TX
Duration:- 6-12 Months
Key Responsibilities
- Design and implement scalable big data architectures using Hadoop, Spark, or other distributed processing frameworks.
- Ingest, store, and manage large volumes of structured and unstructured geospatial data from various sources (e.g., satellite, drone, IoT, APIs).
- Optimize geospatial data storage using formats like GeoParquet, GeoJSON, and PostGIS-enabled databases.
- Develop and maintain ETL/ELT pipelines with a focus on spatial data enrichment, transformation, and aggregation.
- Work with GIS tools and libraries such as GDAL, GeoPandas, Shapely, or QGIS.
- Collaborate with data scientists and analysts to support spatial modeling, analytics, and visualization.
- Implement data quality checks, lineage tracking, and metadata management for geospatial datasets.
- Ensure the performance, scalability, and reliability of geospatial data pipelines in production environments.
Requirements
Technical Skills
- Proficiency in distributed computing frameworks (e.g., Apache Spark, Hadoop, Kafka).
- Strong programming skills in Python, Scala, or Java.
- Experience with spatial databases like PostGIS, GeoMesa, or GeoSpark.
- Familiarity with GIS tools and spatial data formats (e.g., GeoTIFF, KML, shapefiles).
- Cloud platform experience (AWS, Azure, or GCP), especially services like S3, EMR, or BigQuery with geospatial capabilities.
- Understanding of geospatial concepts: coordinate systems, map projections, spatial indexing (R-tree, QuadTree), etc.
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