Find GIS JobsSenior Geospatial Data Engineer
Object Computing
- Location
- Remote (Saint Louis, MO)
- Job type
- Full-time
- Employer type
- Private company
- Posted
- Sep 19, 2025
About the job
Object Computing, Inc. is seeking a Senior Geospatial Data Engineer to join our Xtrack Product Team. In this role, you will lead the design and implementation of scalable, cloud-based geospatial data infrastructures, and play a key part in shaping our data architecture and product engineering strategy with a focus on improving safety and operational efficiencies for organizations in the rail industry. You will work with cutting-edge technologies in image processing, artificial intelligence, cloud computing, and geospatial database management. Your work will optimize complex business processes and unlock new value from large-scale geospatial datasets. What you will do: - Architect, design, and maintain robust, scalable data pipelines and infrastructures for geospatial and big data applications maintaining a focus on performance and the ultimate end-user product experience. - Lead the development and optimization of ETL processes for ingesting, cleaning, transforming, and storing large volumes of geospatial and tabular data. - Design, build, and interact with API-driven, service-to-service web services (using FastAPI, Litestar, Flask, etc.) to enable integration across a suite of products. - Collaborate with backend and platform engineers to ensure secure, reliable, and scalable service-to-service communication. - Translate complex analytics and business questions into actionable, production-grade data solutions. - Collaborate closely with data scientists, analysts, and business stakeholders to deliver high-impact data products. - Drive the adoption and optimization of cloud-based data solutions (e.g., GCP, AWS, Azure). - Ensure data quality, integrity, and security across all stages of the data lifecycle. - Mentor and provide technical guidance to junior data engineers and team members. - Communicate technical details and insights clearly to both technical and non-technical audiences, including leadership. - Proactively recommend and implement improvements to existing data infrastructure and software programs. - Stay current with industry trends and emerging technologies in geospatial data engineering. What you will bring: - An excitement and dedication towards manifesting real and measurable impact for customers and clients and a dedication to being a team player towards achievement of those outcomes. - Experience in software development, data engineering, or big data roles, preferably with a focus on geospatial data. - Experience building solutions with Python. - Experience with relational databases (e.g., SQL), including advanced query building, data extraction, and manipulation. - Experience architecting and optimizing cloud-based data solutions (preferably GCP, AWS, or Azure). - Deep experience with big data technologies such as Hadoop, Spark, MapReduce, or Kafka. - Experience integrating with API-driven, service-to-service web services. - Demonstrated ability to lead projects, mentor team members, and drive technical decisions. - Strong problem-solving skills, resourcefulness, and ability to work independently or collaboratively. - Excellent organizational, interpersonal, and communication skills. What will make you stand out: - Expertise with geospatial libraries and tools (e.g., GDAL, PDAL, PostGIS, GeoPandas, Shapely). - Experience deploying and scaling machine learning (ML) models/algorithms in production. - Strong experience with geospatial analytics and working with geospatial data formats (e.g., LAS, LAZ, COPC, GeoTIFF, Shapefiles). - Experience leading teams in integrating and scaling complex ML/Deep Learning (DL) algorithms. - Experience working with LiDAR data and deriving real-world insights from point clouds. - Experience with ESRI products (ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise) or other GIS platforms. - Experience with data streaming, real-time data processing, or cloud-native geospatial solutions. - Cloud certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Data Analytics). - Experience with OAuth, authentication, and API key management for secure service-to-service communication.
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