BIG DATA ENGINEER SR

$120,001 - $120,001/Yr

SAIC - Halawa, HI

Full-time - Mid Level

Onsite - Halawa, HI

10,001+ employees

Professional, Scientific, and Technical Services

About the position

The Senior Big Data Engineer position at SAIC supports the Joint Fires Network (JFN) initiative, which aims to enhance 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 advanced 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.
• Employ data manipulation and visualization tools to convey current status and historical trends.
• Collaborate with engineers to (re)configure data ingestion pipelines for reliability.
• Work with data in various formats including Excel, CSV, JSON, and XML.
• Support incident management to document and resolve data issues quickly.
• Perform root cause analysis to prevent 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.

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 such as 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.