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.
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:
Availability to work onsite in our St. Louis Office
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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