Lead Mission Data Engineer — Radar & Space Tracking

Saic; Colorado Springs (CO); On-site; USD 120,000 - 160,000; Full time

Job summary

SAIC seeks a Mission Data Engineer to join the GMASS Test & Evaluation team in Colorado Springs, CO, maintaining UEWR and PARCS Ground Based Radars for the United States Space Force. You will build data pipelines, automation, and analysis tools to turn raw radar data into actionable insight.

You will work independently and across multidisciplinary teams to monitor data quality and deliver insights to leadership, using Python, MATLAB, and SQL in a collaborative environment.

Qualifications

• Bachelor’s degree in engineering, physics, CS, math, or related field with 9+ years of experience.
• Active Secret Clearance required.
• 3+ years writing SQL queries and working with relational databases.
• Proficiency with MATLAB for data analysis and tool development.
• Proficiency with Python for data analysis and tool development.

Responsibilities

• Deliver continual data feeds to users and monitor overall data quality, health, and status.
• Design data pipelines from raw sources to SQL databases across Excel, CSV, JSON, and XML formats.
• Develop and maintain software to automate monitoring, transfer, and processing of data.
• Use data manipulation and visualization tools to convey system status and historical trends to leadership.
• Build and expand the toolchain pipeline integrating architecture design, software, and analysis tools using Python, Bash, MATLAB, and SQL.

Skills

Active Secret Clearance

Data engineering experience

Education

Bachelor’s degree in engineering, physics, CS, mathematics, or related field

Tools

SQL

MATLAB

Python

PostgreSQL

Job description

SAIC seeks a Mission Data Engineer to join the GMASS Test & Evaluation team in Colorado Springs, CO, maintaining UEWR and PARCS Ground Based Radars for the United States Space Force. You will build data pipelines, automation, and analysis tools to turn raw radar data into actionable insight.

You will work independently and across multidisciplinary teams to monitor data quality and deliver insights to leadership, using Python, MATLAB, and SQL in a collaborative environment.