Data Engineer – GIS / Geospatial

About You

You are a Data Engineer with strong experience building cloud-based data pipelines and hands-on expertise working with geospatial data. You are comfortable transforming complex operational datasets into reliable and scalable data models and understand how location-based information, GIS systems, road networks, and external data sources integrate within modern cloud data platforms.

You enjoy working in structured engineering environments where data quality, testing, documentation, and maintainability are essential. You can work independently within an established architecture, collaborate effectively with distributed teams, and communicate technical decisions clearly in English.

Note: This is a 4-month temporary opportunity .

Responsibilities

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.; Implement and maintain geospatial data models and transformations in BigQuery.; Work with GIS and ArcGIS-based datasets, including geometry and location-referencing information.; Develop reliable ingestion patterns for REST APIs, feeds, sensor data, and other external sources.; Implement automated validation and data-quality controls across data pipelines.; Troubleshoot data discrepancies, transformation issues, and integration defects.; Support integration testing, data-quality triage, and defect resolution through system acceptance.; Produce clear technical documentation and maintainable code following established engineering standards.; Collaborate with data, application, platform, and other engineering disciplines within a distributed delivery team.; Participate in code reviews, technical discussions, ticketed work, and structured delivery processes.; Use AI-assisted engineering tools responsibly to support development, testing, and troubleshooting.

Requirements

Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or a related field is desired, or equivalent professional experience.; 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.; Ability to maintain at least four hours of daily overlap with U.S. Eastern business hours.; 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.

Nice to have

Experience with transportation, logistics, mapping, mobility, IoT, sensor, or infrastructure-related datasets.; Experience integrating ArcGIS-based sources with cloud data warehouses.; Experience designing geospatial models directly in BigQuery.; Experience with road networks, route segmentation, linear assets, or similar LRS use cases.; Experience ingesting high-volume telemetry, sensor, weather, or map-oriented datasets.