Full-Stack Data Engineer - Mid

Position: Full-Stack Data Engineer
LCAT: Mid
Location: SOUTHCOM HQ, Doral, FL / On-site
Office: U.S. SOUTHERN COMMAND J2

Required clearance: TS/SCI

Required education: Bachelor’s degree in Computer Science, Data Engineering, or a related field, or five (5) years of equivalent experience in full-stack development and data engineering.

Description:

• Develop and maintain the data pipeline infrastructure, ensuring scalable ingestion, transformation, and integration of structured and unstructured datasets within the cloud-based CIP platform.
• Optimize data storage strategies, implementing efficient query execution, indexing, and retrieval techniques for high-volume mission datasets.
• Integrate APIs for secure data sharing across operational environments, ensuring controlled access and compliance with security frameworks.
• Submit the Data Pipeline Optimization Report, detailing improvements in ingestion speed, storage efficiency, and API integrations.
• Integrate all ingestion and transformation workflows with the Identity and Access Management (IAM) framework provisioned under IAM Engineers
• Coordinate with the IAM Engineer team to define required roles, enforce RBAC policies, and maintain compliance with authentication and access standards across IL environments.

• Possess the knowledge and capability to develop, maintain, and optimize data integration pipelines, API services, and front-end interfaces for accessing and visualizing geospatial and structured data.
• Must be proficient in Data Lakes splatforms such as Databricks, Kubernetes, ESRI ArcGIS environments, and cloud-based data engineering.
• Expertise in building scalable, secure web applications, implementing metadata-driven search and retrieval features, and integrating APIs for seamless data interoperability is required.
• Must have demonstrated experience in developing and deploying full-stack applications that enable data visualization, dashboarding, and analytics within ESRI-based GIS platforms, Unity Catalog, and cloud-based databases.
• Must have demonstrated experience in implementing RESTful and GraphQL APIs for seamless data retrieval and integration between Data Lake, ESRI ArcGIS, and external sources.
• Must have demonstrated experience in managing CI/CD pipelines, containerized deployments in Kubernetes, and API authentication mechanisms to ensure secure access to research products.
• Must have demonstrated experience in optimizing database queries and indexing strategies for large-scale geospatial and structured datasets.
  

• AWS Certified Data Analytics – Specialty, Microsoft Certified: Azure Data Engineer Associate, or ESRI ArcGIS Developer Certification.