Geospatial Data Lake Engineer

RPMGlobal

Town of Florida, Northern (NY, KY)

Hybrid

USD 110,000 - 165,000

Full time

4 days ago

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Job summary

Base-2 Solutions seeks a Data Lake Engineer to support USSOUTHCOM J26 ENHANCED DOMAIN AWARENESS. The role involves building, maintaining, and optimizing data integration pipelines, APIs, and front-end interfaces for geospatial and structured data visualization.

The ideal candidate will work with Data Lakes platforms such as Databricks, Kubernetes, and ESRI ArcGIS environments, plus Unity Catalog and cloud-based databases, to deliver scalable web applications and secure API access for analytics

Qualifications

Bachelor's degree in Computer Science, Data Engineering, or a related field.
OR 5 years of equivalent experience in full-stack development and data engineering.
Demonstrated experience developing and deploying full-stack applications for data visualization, dashboarding, and analytics within ESRI-based GIS platforms, Unity Catalog, and cloud-based databases.
Experience implementing RESTful and GraphQL APIs for data retrieval and integration.
Experience managing CI/CD pipelines, containerized deployments in Kubernetes, and API authentication mechanisms.
Experience optimizing database queries and indexing strategies for large-scale geospatial and structured datasets.

Responsibilities

Develop, maintain, and optimize data integration pipelines, API services, and front-end interfaces for geospatial and structured data visualization.
Work with Data Lakes platforms including Databricks, Kubernetes, and ESRI ArcGIS environments.
Build scalable, secure web applications with metadata-driven search and retrieval features.
Integrate APIs for seamless data interoperability.
Develop and deploy full-stack applications enabling data visualization, dashboarding, and analytics within ESRI-based GIS platforms, Unity Catalog, and cloud-based databases.
Implement RESTful and GraphQL APIs for data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources.
Manage CI/CD pipelines, containerized deployments in Kubernetes, and API authentication mechanisms to ensure secure access to research products.
Optimize database queries and indexing strategies for large-scale geospatial and structured datasets.