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# Data Layer Engineer

- **Company:** Prescient Edge
- **Location:** Miami, FL, United States
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Amazon S3, ArcGIS (Software), Batch Processing, Cloud Computing, Cloud Storage, Databases, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Security, GIS Applications, Information Sciences, PostgreSQL, Metadata, Meta-Data Management, Microsoft SQL Server, NoSQL, PostGIS, Role-Based Access Control, Esri GIS (Software), Azure Data Factory, Data Layers, Containerization, Data Lakes, Kubernetes, Information Technology, Collibra, AWS Glue, Data Management, Databricks
- **Published:** October 31, 2026
- **Apply:** https://www.adzuna.com/details/5886452056

## About the Role

* Knowledge and capability to design, implement, and optimize data transformation workflows for geospatial and non-geospatial datasets. Personnel must be proficient in ETL (Extract, Transform, Load) processes, data structuring, and schema management, with expertise in ESRI geospatial data layers, ArcGIS Enterprise, and cloud-based geospatial services.
 * Strong understanding of databases (PostgreSQL/PostGIS, SQL Server, NoSQL), cloud storage solutions (AWS S3, Azure Blob, Google Cloud Storage), and Kubernetes-hosted geospatial applications is required.
 * Demonstrated experience in developing and managing data governance frameworks, implementing metadata and data cataloging solutions, and ensuring compliance with DoD and IC data security policies.
 * Experience with tools such as Databricks Unity Catalog, Collibra, Alation, AWS Glue, or Azure Purview is required.

Education:

 * Bachelor's degree in Data Management, Information Science, Computer Science, or a related field, or five (5) years of equivalent experience in data governance.
 * Desirable but not required certifications include Certified Data Management Professional (CDMP), DAMA Certified Data Governance Professional (DGSP), or Microsoft Certified: Azure Data Engineer Associate.

## Description

* Design and manage a modular data layer architecture that supports scalable ingestion, transformation, and serving of geospatial and structured data across containerized environments.
 * Develop and optimize ETL pipelines for real-time and batch processing of mission-relevant data, ensuring integration with both ESRI and third-party analytic services.
 * Implement metadata management solutions-such as tagging, schema validation, and indexing-to improve lineage tracking and facilitate governance alignment with IL4/IL5 controls.
 * Manage data access enforcement mechanisms, including RBAC policies and encryption controls, consistent with NIST 800-53 Rev. 5, FedRAMP, and DoD cybersecurity mandates.
 * Shall submit the Data Layer Integration & Optimization Report, detailing Kubernetes performance benchmarks related to data lake interaction, data lifecycle strategies for containerized environments, and cloud resource optimization recommendations.