Staff Engineer, Data Analysis (R5290)

What you'll do:

Lead the technical strategy for V-BAT fleet data analysis across fielded aircraft, flight test, simulation, production, and quality workflows 
Own and improve the pipelines that transform raw flight, simulation, and fleet data into reliable engineering metrics, reports, and analysis products 
Conduct fleet-wide studies to identify trends in hardware quality, system performance, reliability, and operational behavior 
Analyze flight-critical sensor performance, GNSS-denied navigation performance, communications behavior, and other aircraft subsystems that are critical to mission success 
Standardize the team’s analysis methods across online tools, Jupyter notebooks, automated Python scripts, and legacy Matlab workflows 
Define best practices for analysis methods, data review, documentation, validation, reproducibility, and contribution workflows 
Build automated Python workflows that make high-value metrics easily accessible to engineering, production, quality, and leadership teams 
Partner with DevOps to build, deploy, maintain, and scale the infrastructure required for automated analysis pipelines and dashboards 
Work with Software, GNC, Embedded, Flight Test, Systems, Production, Quality, and Operations teams to define metrics that reflect aircraft performance and product health 
Support anomaly investigations, root-cause analysis, release readiness, production quality improvements, and customer-impacting fleet investigations with rigorous data analysis 
Mentor engineers on effective data analysis practices and raise the quality bar for data-driven engineering decisions across the V-BAT team 

Required qualifications:

5+ years of relevant experience with a Bachelor’s degree in Computer Science, Data Science, or a related technical field 
Strong Python skills and experience building data analysis tools, automated analysis workflows, or data pipelines 
Experience analyzing data from fielded physical products such as aerospace systems, automotive systems, robotics platforms, commercial electronics, IoT devices, industrial equipment, or similarly complex real-world systems 
Experience working with large, messy datasets from deployed products, test events, simulations, production systems, or operational environments 
Ability to translate ambiguous engineering questions into structured analysis, sound conclusions, and clear recommendations 
Strong communication skills and the ability to influence cross-functional engineering, production, quality, and operations teams 

Preferred qualifications:

Experience with flight test data, aircraft telemetry, UAVs, robotics, autonomy, embedded systems, GNC, navigation systems, communications systems, or aerospace sensor suites 
Experience with Matlab, Jupyter, or similar analysis and visualization tools 
Experience building production-quality dashboards, automated reports, data products, or fleet-health monitoring systems 
Experience with databases, cloud storage, data lake architectures, time-series databases, telemetry systems, or data cataloging 
Experience with anomaly detection, trend analysis, statistical process control, reliability analysis, regression detection, or automated validation of complex systems