Data Engineer – GIS / Geospatial

Role Overview

You will be a Data Engineer with strong experience building cloud-based data pipelines and hands-on expertise working with geospatial data. You will design, build, test, and maintain ingestion pipelines for operational and geospatial data sources, develop transformations that connect source datasets with standardized geographic and road-network references, and implement and maintain geospatial data models and transformations in BigQuery.

What You Will Do

Your main day-to-day responsibilities will include designing and building ETL/ELT pipelines, integrating APIs or external data sources into cloud data platforms, and implementing automated data validation, reconciliation, and data-quality controls. You will also work with GIS and ArcGIS-based datasets, including geometry and location-referencing information, and develop reliable ingestion patterns for REST APIs, feeds, sensor data, and other external sources.

Why It Might Be a Fit

You will be a fit for this role if you have 4+ years of professional experience in Data Engineering, strong production experience with Python, SQL, and GCP, particularly BigQuery and Cloud Composer / Apache Airflow, and hands-on experience working with geospatial/GIS data, ArcGIS or comparable GIS technologies, and spatial data transformations.

Requirements

• Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or a related field
• 4+ years of professional experience in Data Engineering or similar roles
• Strong hands-on production experience with Python and SQL for data engineering
• Production experience with Google Cloud Platform (GCP), particularly BigQuery, Cloud SQL, and Cloud Composer / Apache Airflow
• Experience designing, building, and maintaining ETL/ELT pipelines and cloud-based data transformations
• Hands-on production experience working with geospatial and GIS data
• Experience with the ArcGIS ecosystem and/or comparable enterprise GIS technologies
• Understanding of Linear Referencing Systems (LRS), road-network data, route segmentation, or comparable linear geospatial models
• Experience working with GeoJSON, geometry/geography data types, spatial transformations, and spatial SQL
• Experience integrating REST APIs, operational feeds, and third-party data sources into data platforms
• Strong understanding of relational and analytical data modeling
• Experience implementing automated data validation, reconciliation, and data-quality controls
• Strong testing and technical documentation practices
• Proficiency with Git and collaborative software development workflows
• Experience using modern AI-assisted development tools such as Claude Code or equivalent, with the ability to appropriately validate generated output
• Strong written and spoken English, with the ability to collaborate effectively with distributed engineering teams

Benefits

• 4+ years of professional experience in Data Engineering
• Strong production experience with Python, SQL, and GCP, particularly BigQuery and Cloud Composer / Apache Airflow
• Hands-on experience working with geospatial/GIS data, ArcGIS or comparable GIS technologies, and spatial data transformations
• Experience building ETL/ELT pipelines and integrating APIs or external data sources into cloud data platforms
• Strong English proficiency and ability to maintain at least four hours of daily overlap with U.S. Eastern business hours