Full-Stack Data Engineer - Mid

Join the Nalley Consulting team at Southcom HQ. 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. Required Experience 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 platforms 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. Desired Qualifications AWS Certified Data Analytics – Specialty, Microsoft Certified: Azure Data Engineer Associate, or ESRI ArcGIS Developer Certification. #J-18808-Ljbffr