Posted
30 Sep 2026
Last seen
01 Oct 2026
Location
United States
Lifecycle
fresh
Grade
D
Why this grade
This listing scored 54/100, which is a D. It lost the most ground on pay transparency.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Data Science Developer Senior Full Time
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.
Originally posted on Himalayas
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Where this listing came from
- 01 Oct 2026 Himalayas first sighting
Seen on 1 board over 0 days.