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Skills
Analysis Skillsunmatched
Cryptographyunmatched
Data Managementunmatched
Database Extract Transform and Load (ETL)unmatched
ESRIunmatched
Federal Governmentunmatched
Health Planunmatched
Internet Securityunmatched
Metadataunmatched
Spatial Dataunmatched
Structured Dataunmatched
U.S. National Institute of Standards and Technology (NIST)unmatched
United States Department of Defense (DoD)unmatched
Description
Prescient Edge is seeking a Data Layer Engineer to support a Federal Government client.
Please note that the availability of this position is contingent upon contract award.
Benefits:
At Prescient Edge, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best-in-class benefits package that includes:
A competitive salary with performance bonus opportunities.
Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage.
A substantial retirement plan with no vesting schedule.
Career development opportunities, including on-the-job training, tuition reimbursement, and networking.
A positive work environment where employees are respected, supported, and engaged.
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.