Vacancy expired!
- Lead Design, implementation and management of Agency wide Data Abstraction layer
- Design and implement effective database solution to Ingest, curate, store and retrieve agency/IC data.
- Perform structural data tests in alignment with user and application usage patterns.
- Standardize data architecture and data management practices.
- Implement database controls in alignment with internal and external regulations.
- Drive and manage operational data standards.
- Define structure, integrate, govern, describe and model data in the NGA enterprise
- Design and implement effective data architecture and data management practices to support NGA enterprise applications and physical data modeling according to project requirements
- Develop architectural strategies for data modeling, design and implementation to meet stated requirements for metadata management, operational data stores and Extract Transform Load environments
- Participates in team discussions regarding data acquisitions, archive recovery, and implementation of NGA Data Lakes and Warehouses
- Review existing data architectures to determine overall effectiveness and compliance with CDO/DCDO objectives, develop comprehensive strategies for improving underachieving areas and present these plans to CDO & DCDO
- Participates in NGA/IC driven Data Standards committees
- Support database administrators, network designers and IT personnel to create effective and secure methods for data backup and recovery
- Document data inventory and data flow diagrams to determine what can be measured and consumed, when and how
- Bachelor's degree in mathematics, statistics, computer science or related field, or equivalent Senior level experience as Data Architect.
- Demonstrated 12+ Experience in Data management, Data modeling and/or Data Ontologies
- 3+ Years of experience with AWS cloud services
- Experience in structured, semi-structured and structured datasets
- Experience with Linux/Unix, Python, Scala, SQL scripting
- Experience MPP (Massively Parallel Processing) platforms
- Experience of MPP (Massively Parallel Processing) platforms
- Experience employing Extract Transform Load (ETL) techniques to blend data from multiple sources
- Experience in Machine Learning, Artificial Intelligence, Natural Language Processing
- Experience in GEOINT domains and datasets
Vacancy expired!