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SAIC - Halawa, HI
posted 2 months ago
Full-time - Mid Level
Onsite - Halawa, HI
10,001+ employees
Professional, Scientific, and Technical Services
About the position
The Big Data Engineer position at SAIC supports the Joint Fires Network (JFN) initiative, aimed at enhancing Multi-Domain Joint Command and Control capabilities. The role involves developing, deploying, and continuously improving the JFN system to ensure effective data management and reporting during critical conflicts. The engineer will work closely with various teams to ensure data quality and reliability, utilizing a range of data manipulation and visualization tools.
Responsibilities
- Provide expert support to improve Multi-Domain Joint Command and Control capabilities.
- Deliver continual data feeds to users and monitor data quality and ingest health.
- Visualize, interpret, and report data findings in dynamic reports.
- Collaborate with other engineers to configure data ingestion pipelines for reliability.
- Work with data in various formats including Excel, CSV, JSON, and XML.
- Support incident management processes and perform root cause analysis for data outages.
- Develop and maintain software for monitoring real-time data feeds and alerting on issues.
- Support the design and implementation of web-based collaboration tools for data reporting.
- Demonstrate proficiency in scripting languages such as Python or Bash.
- Utilize open-source analytics and visualization applications for system performance monitoring.
Requirements
- Minimum five (5) years of data analysis/engineering experience.
- Minimum two (2) years of general IT support experience.
- Bachelor of Science in Computer Science, Mathematics, Electrical Engineering, Physics, Information Systems, or Information Technology.
- Active TS/SCI clearance.
Nice-to-haves
- Experience with Intelligence and Command & Control (C2) datasets including ELINT, COMINT, MASINT, and GEOINT.
- Knowledge in data mining, data modeling, statistics, and machine learning.
- Familiarity with deploying and managing container management via Kubernetes clusters.
