Senior Geospatial Data Engineer

Saint Louis, Missouri
Data Insights – Data Engineer /
Full Time /
Remote
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.